perf(shell): route local products through MKL and reduce Hessian storage work
This commit is contained in:
KOKO\Mimi
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# Shell 계산 경로의 성능 변경
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이 기록은 reduced-coordinate shell의 local 계산 변경과 근거를 구분한다.
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전체 시간 목표와 최종 원본 비교는 [PRD](PRD.md)의 계약이며 아래의 단계 검사는
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그 계약의 최종 합격을 대신하지 않는다.
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## 계측과 변경의 연결
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원본 meshfine shell의 기준 전체 실행은 6372.3256209초다. VTune 소프트웨어
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샘플링의 별도 150초 부분 수집은 accepted increment 2 / time 0.2까지 포함한다.
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`Jet*`는 sampled CPU 133.466초(27.6%), `malloc`은 30.289초(6.3%)였다.
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`EvaluateAssembly`의 inclusive 257.862958 CPU초와 중첩 selector의 1.600014초는
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겹치는 호출 경로이므로 더하거나 전체 경과 시간으로 바꾸지 않는다.
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`nonlinear_mitc4_shell.cpp`의 모든 Jet는 기존에 값이 상수인 경우도 576-double
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Hessian을 영 초기화한 `shared_ptr`로 할당했다. 상수의 영 Hessian은 이제
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읽기 전용 정적 영 배열을 참조하고 처음 쓰는 때만 기존 공유 storage를 할당한다.
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읽기 전용 영 배열에는 trial 값이 없으며 동시 호출은 그 배열을 수정하지 않는다.
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이미 할당된 Hessian의 복사/공유 수명은 그대로다. 현재 trial 이외의 형상·접선·
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도함수 응답을 저장하거나 주소에 따라 재사용하는 cache는 추가하지 않았다.
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후속 후보는 576-entry 반복문 앞에서 입력 read pointer와 fresh output pointer를
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한 번씩 취득한다. fresh output은 단일 `make_shared` 할당을 유지하고 영 초기화를
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생략한 뒤 576개 전체를 기록한다. `operator+/-/*`, scalar scale, Compose, Atan2의
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모든 complete write와 MKL 거부 시의 NaN fill 뒤에만 결과를 읽거나 복사한다.
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일반 부분 mutable write는 영 초기화를 유지한다. 상수의 nullptr 복사에는 별도
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mutable 공유 객체가 없지만 실제 consumer는 복사된 상수 Hessian을 수정하지 않는다.
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이미 할당된 결과의 shared copy와 입력 alias는 수정하지 않는다.
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## 일반 행렬 연산의 MKL 경계
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| 파일 / 함수 | 연산과 크기 | 변경 |
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| --- | --- | --- |
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| `mitc4_shell.cpp::Stiffness`, `Congruence` | 5×20 strain의 BᵀCB, 20/4 local→24 congruence | `Matrix::Multiply`와 private transpose-left MKL GEMM, 상삼각 결과를 그대로 대칭 복사 |
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| `nonlinear_mitc4_inertia.cpp::CheckPhysicalMass` | 24×20 complement Gram·mass congruence, 20×20 Cholesky·inverse·reconstruction | GEMM 및 기존 private LAPACK helper; 같은 positivity, reconstruction, 2^-32 conditioning gate 유지 |
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| `nonlinear_mitc4_inertia.cpp::Evaluate` | 각 lumped mass-node의 6×3 coefficient Gram, velocity/position bilinear, 3방향 mass variation의 6×6 block | 무할당 row-major transpose-right GEMM; 원래 point/node/row/column scatter와 가중 누적 유지 |
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| `nonlinear_mitc4_shell.cpp::operator*`, `Compose`, `Atan2`, `DrillingEnergy` | ordinary 24×24 derivative outer products | private `OuterProduct`의 row-major GEMM k=1, 기존 Jet storage에 직접 기록 |
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| `hht_dynamic_algebra.cpp::BuildPhysicalSpace` | scaled free mass×analytic null 및 일반 complement congruence의 sparse contributions | entrywise compact-diagonal MKL products 뒤 원래 CSR/COO 순서 누적; full global dense matrix 없음 |
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| `hht_dynamic_algebra.cpp::CheckLocalMass` | nonempty nodal physical block, 크기1–6 | MKL Cholesky/inverse; 동일 inverse infinity norm과 2^-32 conditioning 검사 |
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| `hht_dynamic_algebra.cpp::CheckRegularity`, `hht_reduced_operators.cpp::CheckGraphRegularity` | scalar null stiffness metric와 gradient×null projection | MKL GEMV/dot 또는 entry products, 기존 fresh factorization/모든 unit RHS/residual/condition gate 유지 |
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| `hht_reduced_operators.cpp::ContractConstraintHessian` | failure-only bilinear replay의 sparse Hessian entries | 두 MKL diagonal product 뒤 기존 left association/entry order sum |
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Outer product는 배열 copy나 Matrix 객체를 만들지 않는다. 크기·integer range·
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nonempty null storage를 검사하며 비유한 입력은 MKL 호출/출력 쓰기 전에 거부한다.
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유한 입력의 곱 overflow는 후속 owner finite gate가 판단한다. Jet consumer는
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거부된 operand의 결과를 NaN으로 표시하고 원래 equilibrium/constraint finite
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실패를 반환한다. 직접 scalar product로 계산하는 fallback은 없다.
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`CholeskyLowerAndInverse`의 optional private failure reason은 validation 전에
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`kNone`으로 초기화된다. factor pivot/finite 실패와 inverse/finite 실패를 구분하여
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기존 positive-mass와 ill-conditioned-mass 진단을 유지한다. 실패에서는 lower와
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inverse output candidate를 교체하지 않는다. 기존 default-nullptr consumer의
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bool 의미는 그대로이며 live inverse 실패를 발생시킨 검사는 아직 없다.
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Element-local dense work의 `ScopedLocalDenseThreads`는 caller TLS 요청이 default
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0일 때만 1을 적용한다. caller의 양수 override는 유지하고 정상 반환과 unwind 뒤
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원래 default를 복원한다. 전역 MKL/OpenMP 정책이나 이후 global solve에는 영향을
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주지 않는다. 각 scalar metric scope는 MKL 호출 뒤 끝나며 global PARDISO를 포함하지
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않는다. 현재 후보의 실제 비용과 복원 검사는 아래 단계 검증 기록으로 구분한다.
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TLS default 0, caller override 우선순위와 저장한 값을 복원하는 동작은
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[Intel 2026 thread-local reference](https://www.intel.com/content/www/us/en/docs/onemkl/developer-reference-c/2026-0/mkl-set-num-threads-local.html)의 계약을 따른다.
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Hessian의 합산 순서와 ordinary product는 별도다. 곱셈 Jet는 원래의
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`left.second * right.value + outer1 + outer2 + left.value * right.second`를
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유지한다. Compose와 Atan2는 계수×gradient를 먼저 계산하여 원래 left association을
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유지한 뒤 outer product를 계산한다. GEMM의 연산과 signed-zero 결과는 원래 scalar
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구현의 bit 동일성을 주장하지 않으며 접선/방향/혼합 도함수의 수치 검토 대상이다.
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일반 24×24 연산을 AD라는 이유로 특수 정밀도 예외로 처리하지 않는다.
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## 유지하는 특수 연산
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| 파일 / 함수 | 크기·정밀도·이유 | 검증 범위 |
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| --- | --- | --- |
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| `nonlinear_mitc4_inertia.cpp::Jet`, `ExpSkew`, `LeftJacobian` | 3개의 nodal rotation coordinate에 대한 최대 3차 analytic derivative; 3×3×3 tensor | finite rotation, inertia force/position/velocity tangent와 null·momentum oracle |
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| `hht_reduced_operators.cpp::BasisValue`, fixed basis 생성 | normalized high+low 및 outward radius; 3-vector basis certificate | fixed chart/radius replay·partial-boundary·selector transversality |
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| `hht_reduced_operators.cpp::RateSum`, `GradientDot`, reduced block 누적 | sparse support의 원래 순서 Neumaier correction | cancellation, full defect, mixed rates·channel acceptance |
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| `nonlinear_mitc4_inertia.cpp::InertiaSum` | kinetic force/energy/momentum의 원래 순서 compensated contraction | 독립 inertia oracle와 omission 검출, 좌표/단위 변화 |
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| shell의 fixed3 coordinate tensor/rotation 변환 | 좌표·director·chart의 3-vector 또는 3×3 연산 | rigid motion/objectivity·principal chart 실패 |
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| `hht_dynamic_algebra.cpp::BuildPhysicalSpace`의 analytic nodal basis Gram, `InitializeAcceleration`의 force projection/lift | translation 1계수 또는 단일 절점의 최대3 rotation components; 현재 assembly의 nodal frame에 대한 Float64 좌표 변환 | 서로 다른 node의 basis support는 disjoint, 같은 node의 최대3-vector inner product만 사용; excluded fixed rows·원래 association·초기 acceleration 진단 순서 유지 |
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보상 누적과 interval/basis 인증은 일반 Float64 GEMM으로 접어 수치 의미를 잃지 않는다.
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`hht_reduced_operators.cpp::GradientDot`, `Lift`, `ProjectPhysical`,
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`ReconstructPhysicalRates`, `AssembleAugmentedReducedSystem`의 support contractions는
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원래 entry 순서의 Neumaier correction과 high+low/outward fixed-basis certificate를
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유지하는 예외다. Plain sum과 달리 partition cancellation에서 소실되는 1을 유지하는
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`ReconstructsRatesAcrossSelectedPartitionCancellation` 및 augmented full-model defect
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검사가 해당 의미를 검증한다. 일반 24×24 outer와 mass matrix 제품은 이 예외로 묶지 않는다.
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`BuildPhysicalSpace`의 좌표 basis는 현재 assembly의 analytic null로 각 호출에서
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생성한다. 초기화는 initial assembly를 사용하고 후속 질량 인증은 해당 현재 assembly를
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사용한다. 실행 전체의 fixed initial chart와 같은 자료라고 판단하지 않으며
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다른 trial에 basis/응답을 재사용하지 않는다.
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## 단계 검증 상태
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변경 전 clean source `8c7c41729eb9eaa904f6739b54d34c37b1bd555f`의 fresh MSVC
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Debug configure/build는 native 0, local shell/inertia/reduced/math 70개는 모두 PASS다.
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별도 MITC4 linear kernel·mass·recovery 20개도 native 0으로 모두 PASS다.
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Mixed-time actual shell fixture는 144.84초에 정상 통과했으며 중단되지 않았다.
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[원래 실행 기록](../../.harness/performance/t4/baseline-native.json)과
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[linear 실행 기록](../../.harness/performance/t4/baseline-linear-native.json)을 보존한다.
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첫 후보 build의 `Status` 기본 생성자 오류(native 2)는 별도로 보존하고
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`Status::Ok` 초기화로 수정했다. 수정 후보의 configure/build는 native 0이고
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91개 중 90 PASS, `HhtReducedEmbedding.ReconstructsActualShellRatesWithMixedTimeLoad`는
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180초 timeout으로 미통과다. 전체 CTest native 8과 실제 종료 상태를 보존한다.
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이 Debug 비용 악화를 Release 개선으로 표시하지 않는다. 이는
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`candidate-local-fixed` snapshot의 결과다. Read pointer hoist, fresh output의
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단일 allocation/full overwrite, 별도 이름의 local TLS scope와 추가 coverage를
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적용한 `packed-output-mkl-coverage` 결과는 별도로 기록한다.
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기존 Korean compiler 환경의 Ninja header prefix가 mojibake이고 actual dependency
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graph가 0개인 사실을 확인했다. 그 build의 직접 변경 source/검사 결과는 보존하되
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header consumer 전체 재빌드를 입증한다고 해석하지 않는다. 설치된 compiler의
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locale fallback 때문에 `VSLANG=1033`만으로 해결되지 않는다는 root의 후속 근거가
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있다. 정확한 include prefix를 지정한 ignored metadata helper의 별도 probe 뒤
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full fresh build에서 actual Ninja header deps를 확인했다. 공용 preset/flag나
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source object를 바꾸어 혼합하지 않는다.
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후속 `packed-output-mkl-coverage` snapshot의 source SHA-256은
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[source manifest](../../.harness/performance/t4/candidate-packed-source.json)에 있다.
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Corrected-prefix fresh configure/build는 각각 native 0이고
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`eigen_reduction.cpp.obj`의 실제 dependency inventory에
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`dense_blas_internal.h`가 포함되어 있다.
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기존 Cholesky/eigen consumer, local tangent/objectivity/patch·inertia,
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fixed chart·channel/failure·boundary·MKL scope/shape/finite 검사 **105/105 PASS**,
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native 0, CTest 36.94초다. 별도 mixed-time fixture도 **1/1 PASS**, native 0,
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fixture 60.69초다. [실행 기록](../../.harness/performance/t4/packed-native.json),
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[검사 로그](../../.harness/performance/t4/packed-4.txt),
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[mixed-time 기록](../../.harness/performance/t4/packed-mixed-native.json)을 보존한다.
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이 106개 결과는 전체 Debug/원본 비교/시간수렴을 통과했다는 뜻이 아니다.
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첫 Release 보조 configure는 runtime DLL PATH를 compiler 탐색보다 앞에 두어
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icx가 선택되었고 `libircmt.lib` 없음으로 native 1 실패했다. 수치 실행은 없었으며
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실패 자료/cache를 보존한다. 동일 설치 MSVC cl을 명시한 별도 fresh directory의
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Release configure/build 97 edges는 native 0이다. [보조 실행 기록](../../.harness/performance/t4/release-micro-fixed-native.json)을 보존한다.
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Jet 보조 측정은 frozen `8c7c417`의 실제 Jet source span과 현재 production
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`nonlinear_mitc4_shell.cpp`를 같은 translation unit에 두고 현재 source의
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Release library와 연결했다. 동일 입력·flags로 각 variant의 3000-product loop를
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워밍업 없이 한 번씩 측정했다. 모든 value/gradient/Hessian/directional/mixed
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coefficient 및 checksum이 같고 실제 native 0, scope 안 effective threads 1,
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종료 뒤 caller TLS 복원 true다. 정확성 대조는 모든 타이밍 후 수행했다.
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| 보조 variant | 3000-product loop 경과 시간 |
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| --- | ---: |
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| frozen original | 0.0025384초 |
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| MKL candidate / default 8 | 0.0082295초 |
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| MKL candidate / element scope 1 | 0.0029779초 |
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Scope는 새 MKL kernel의 default-thread 비용을 줄이지만 이 dense nonzero
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kernel 자체가 원래 구현보다 빠르다는 근거는 아니다. Scope 후보도 original보다
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약17% 느리다. 전체 모델의 준비·조립·allocator·선형 해법·출력 비용과 최종
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100초 목표는 이 보조 값으로 판단하지 않는다. 실제 production의 Constant/Jet
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allocation 빈도 감소는 최종 VTune에서 확인해야 한다.
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Standalone include의 vendor C4819 경고는 보존했다. 실제 production과 같은
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`/W4 /WX /external:W0`로 compile/link만 추가 실행하여 native 0/경고 없음이고
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수치 타이밍은 반복하지 않았다. 측정된 exe는 별도 원본 copy로 보존했으며
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추가 exe의 `.text` SHA-256이 동일한 것을 확인했다.
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[기계어/실행 파일 보존 기록](../../.harness/performance/t4/micro-warning-policy-text-comparison.json)을 따른다.
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전체 Debug·원본 비교·C08 current grid·VTune 최종 수집·공식 단일 시간 측정은
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이 단계에서 실행하지 않았다. 변경되지 않은 reference와 tolerance를 사용해야 한다.
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@@ -2,9 +2,11 @@
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#include <array>
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#include <cmath>
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#include <cstddef>
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#include <exception>
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#include <iomanip>
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#include <limits>
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#include <sstream>
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#include <stdexcept>
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#include <string>
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#include <utility>
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#include <vector>
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@@ -13,6 +15,7 @@
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#include "fesa/math/matrix.h"
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#include "fesa/solvers/linear/linear_solver.h"
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#include "fesa/solvers/linear/tangent_solver.h"
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#include "math/dense_blas_internal.h"
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namespace fesa {
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namespace hht_internal {
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@@ -132,13 +135,13 @@ Status CheckLocalMass(const Domain& domain, const SparseMatrix& matrix,
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const std::size_t begin, const std::size_t end) {
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if (begin == end) return Status::Ok();
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const std::size_t size = end - begin;
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std::array<std::array<double, 6>, 6> block{};
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std::array<std::array<double, 6>, 6> lower{};
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const dense_blas_internal::ScopedLocalDenseThreads local_threads{};
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Matrix block{size, size};
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double scale = 0.0;
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for (std::size_t i = 0; i < size; ++i) {
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for (std::size_t j = 0; j < size; ++j) {
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block[i][j] = Entry(matrix, begin + i, begin + j);
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scale = std::max(scale, std::abs(block[i][j]));
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block(i, j) = Entry(matrix, begin + i, begin + j);
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scale = std::max(scale, std::abs(block(i, j)));
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}
|
||||
}
|
||||
if (!std::isfinite(scale) || !(scale > 0.0)) {
|
||||
@@ -149,36 +152,34 @@ Status CheckLocalMass(const Domain& domain, const SparseMatrix& matrix,
|
||||
for (std::size_t i = 0; i < size; ++i) {
|
||||
double sum = 0.0;
|
||||
for (std::size_t j = 0; j < size; ++j) {
|
||||
block[i][j] /= scale;
|
||||
sum += std::abs(block[i][j]);
|
||||
block(i, j) /= scale;
|
||||
sum += std::abs(block(i, j));
|
||||
}
|
||||
norm = std::max(norm, sum);
|
||||
for (std::size_t j = 0; j <= i; ++j) {
|
||||
double value = block[i][j];
|
||||
for (std::size_t k = 0; k < j; ++k) value -= lower[i][k] * lower[j][k];
|
||||
if (!std::isfinite(value) || (i == j && !(value > 0.0))) {
|
||||
return Failure(
|
||||
domain, "dynamic-positive-mass",
|
||||
"Physical mass requires strictly positive Cholesky pivots.");
|
||||
}
|
||||
lower[i][j] = i == j ? std::sqrt(value) : value / lower[j][j];
|
||||
}
|
||||
}
|
||||
Matrix lower{size, size};
|
||||
Matrix inverse_lower{size, size};
|
||||
auto factor_failure = dense_blas_internal::CholeskyFailure::kNone;
|
||||
try {
|
||||
if (!dense_blas_internal::CholeskyLowerAndInverse(
|
||||
block, lower, inverse_lower, &factor_failure)) {
|
||||
if (factor_failure == dense_blas_internal::CholeskyFailure::kInverse)
|
||||
return Failure(
|
||||
domain, "dynamic-positive-mass-conditioning",
|
||||
"A nodal free physical block reciprocal condition is below 2^-32.");
|
||||
return Failure(
|
||||
domain, "dynamic-positive-mass",
|
||||
"Physical mass requires strictly positive Cholesky pivots.");
|
||||
}
|
||||
} catch (const std::exception& error) {
|
||||
return Failure(domain, "dynamic-positive-mass", error.what());
|
||||
}
|
||||
const Matrix inverse =
|
||||
dense_blas_internal::MultiplyTransposeLeft(inverse_lower, inverse_lower);
|
||||
std::array<double, 6> sums{};
|
||||
for (std::size_t column = 0; column < size; ++column) {
|
||||
std::array<double, 6> solution{};
|
||||
for (std::size_t i = 0; i < size; ++i) {
|
||||
double value = i == column ? 1.0 : 0.0;
|
||||
for (std::size_t k = 0; k < i; ++k) value -= lower[i][k] * solution[k];
|
||||
solution[i] = value / lower[i][i];
|
||||
}
|
||||
for (std::size_t reverse = size; reverse > 0U; --reverse) {
|
||||
const std::size_t i = reverse - 1U;
|
||||
double value = solution[i];
|
||||
for (std::size_t k = i + 1U; k < size; ++k)
|
||||
value -= lower[k][i] * solution[k];
|
||||
solution[i] = value / lower[i][i];
|
||||
sums[i] += std::abs(solution[i]);
|
||||
sums[i] += std::abs(inverse(i, column));
|
||||
}
|
||||
}
|
||||
const double inverse_norm = *std::max_element(sums.begin(), sums.end());
|
||||
@@ -212,19 +213,33 @@ Result<PhysicalSpace> BuildPhysicalSpace(
|
||||
double symmetry_error = 0.0;
|
||||
double null_error = 0.0;
|
||||
if (mass_scale > 0.0) {
|
||||
Vector normalized_mass{mass.Values().size()};
|
||||
Vector null_coefficients{mass.Values().size()};
|
||||
for (std::size_t index = 0U; index < mass.Values().size(); ++index) {
|
||||
normalized_mass[index] = mass.Values()[index] / mass_scale;
|
||||
const auto full = dofs.FreeDofs()[mass.ColumnIndices()[index]];
|
||||
if (full % 6U >= 3U && node_null[full / 6U] != no_null)
|
||||
null_coefficients[index] =
|
||||
assembly.rotations[full / 6U].drill_null[full % 6U - 3U];
|
||||
}
|
||||
Vector null_products{0U};
|
||||
{
|
||||
const dense_blas_internal::ScopedLocalDenseThreads local_threads{};
|
||||
null_products = dense_blas_internal::MultiplyDiagonal(normalized_mass,
|
||||
null_coefficients);
|
||||
}
|
||||
for (std::size_t row = 0; row < mass.Rows(); ++row) {
|
||||
std::vector<double> action(null_nodes.size(), 0.0);
|
||||
for (std::size_t index = mass.RowOffsets()[row];
|
||||
index < mass.RowOffsets()[row + 1U]; ++index) {
|
||||
const std::size_t column = mass.ColumnIndices()[index];
|
||||
const double entry = mass.Values()[index] / mass_scale;
|
||||
const double entry = normalized_mass[index];
|
||||
mass_norm = std::hypot(mass_norm, entry);
|
||||
symmetry_error = std::hypot(
|
||||
symmetry_error, entry - Entry(mass, column, row) / mass_scale);
|
||||
const std::size_t full = dofs.FreeDofs()[column];
|
||||
if (full % 6U >= 3U && node_null[full / 6U] != no_null) {
|
||||
action[node_null[full / 6U]] +=
|
||||
entry * assembly.rotations[full / 6U].drill_null[full % 6U - 3U];
|
||||
action[node_null[full / 6U]] += null_products[index];
|
||||
}
|
||||
}
|
||||
for (const double value : action)
|
||||
@@ -291,6 +306,7 @@ Result<PhysicalSpace> BuildPhysicalSpace(
|
||||
}
|
||||
}
|
||||
std::vector<CooContribution> entries;
|
||||
std::vector<std::pair<double, double>> mass_factors;
|
||||
node_starts.push_back(dimension);
|
||||
double complement_gram_error = 0.0;
|
||||
double null_gram_error = 0.0;
|
||||
@@ -350,8 +366,10 @@ Result<PhysicalSpace> BuildPhysicalSpace(
|
||||
domain, "dynamic-invalid-analytic-null",
|
||||
"The scaled physical and analytic null Gram identities failed."));
|
||||
}
|
||||
for (std::size_t i = 0; i < dimension; ++i)
|
||||
for (std::size_t i = 0; i < dimension; ++i) {
|
||||
entries.push_back({i, i, 0.0, 0U, entries.size()});
|
||||
mass_factors.push_back({0.0, 0.0});
|
||||
}
|
||||
for (std::size_t row = 0; row < mass.Rows(); ++row) {
|
||||
const auto& left = rows[dofs.FreeDofs()[row]];
|
||||
for (std::size_t index = mass.RowOffsets()[row];
|
||||
@@ -359,13 +377,54 @@ Result<PhysicalSpace> BuildPhysicalSpace(
|
||||
const auto& right = rows[dofs.FreeDofs()[mass.ColumnIndices()[index]]];
|
||||
for (const auto& a : left) {
|
||||
for (const auto& b : right) {
|
||||
entries.push_back({a.first, b.first,
|
||||
a.second * mass.Values()[index] * b.second, 0U,
|
||||
entries.size()});
|
||||
entries.push_back({a.first, b.first, a.second, 0U, entries.size()});
|
||||
mass_factors.push_back({mass.Values()[index], b.second});
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
Vector coefficients{entries.size()};
|
||||
Vector mass_values{entries.size()};
|
||||
Vector right_values{entries.size()};
|
||||
for (std::size_t i = 0U; i < entries.size(); ++i) {
|
||||
coefficients[i] = entries[i].value;
|
||||
mass_values[i] = mass_factors[i].first;
|
||||
right_values[i] = mass_factors[i].second;
|
||||
}
|
||||
Vector projected{0U};
|
||||
{
|
||||
const dense_blas_internal::ScopedLocalDenseThreads local_threads{};
|
||||
projected =
|
||||
dense_blas_internal::MultiplyDiagonal(coefficients, mass_values);
|
||||
bool finite = true;
|
||||
for (std::size_t i = 0U; i < projected.Size(); ++i) {
|
||||
entries[i].value = projected[i];
|
||||
finite = finite && std::isfinite(projected[i]);
|
||||
}
|
||||
// A rejected intermediate cannot produce a finite original contribution.
|
||||
// Still compute the remaining finite entries so an earlier final-product
|
||||
// overflow keeps its diagnostic priority. No invalid operand reaches MKL.
|
||||
if (!finite) {
|
||||
std::vector<std::size_t> valid_positions;
|
||||
for (std::size_t i = 0U; i < projected.Size(); ++i)
|
||||
if (std::isfinite(projected[i])) valid_positions.push_back(i);
|
||||
Vector valid_left{valid_positions.size()};
|
||||
Vector valid_right{valid_positions.size()};
|
||||
for (std::size_t i = 0U; i < valid_positions.size(); ++i) {
|
||||
valid_left[i] = projected[valid_positions[i]];
|
||||
valid_right[i] = right_values[valid_positions[i]];
|
||||
}
|
||||
const Vector valid_products =
|
||||
dense_blas_internal::MultiplyDiagonal(valid_left, valid_right);
|
||||
for (std::size_t i = 0U; i < valid_positions.size(); ++i)
|
||||
entries[valid_positions[i]].value = valid_products[i];
|
||||
auto rejected = MakeSparse(dimension, dimension, std::move(entries));
|
||||
return Result<PhysicalSpace>::Failure(rejected.GetStatus());
|
||||
}
|
||||
projected = dense_blas_internal::MultiplyDiagonal(projected, right_values);
|
||||
}
|
||||
for (std::size_t i = 0U; i < entries.size(); ++i)
|
||||
entries[i].value = projected[i];
|
||||
auto block = MakeSparse(dimension, dimension, std::move(entries));
|
||||
if (!block.HasValue())
|
||||
return Result<PhysicalSpace>::Failure(block.GetStatus());
|
||||
@@ -436,15 +495,20 @@ Result<Regularity> CheckRegularity(const Domain& domain,
|
||||
for (std::size_t i = 0; i < nodes.size(); ++i) {
|
||||
node_null[nodes[i]] = i;
|
||||
const auto& n = assembly.rotations[nodes[i]].drill_null;
|
||||
double stiffness = 0.0;
|
||||
Matrix metric{3U, 3U};
|
||||
Vector direction{3U};
|
||||
for (std::size_t a = 0; a < 3; ++a) {
|
||||
direction[a] = n[a];
|
||||
for (std::size_t b = 0; b < 3; ++b) {
|
||||
stiffness += n[a] *
|
||||
Entry(assembly.drilling_metric, 6U * nodes[i] + 3U + a,
|
||||
6U * nodes[i] + 3U + b) *
|
||||
n[b];
|
||||
metric(a, b) = Entry(assembly.drilling_metric, 6U * nodes[i] + 3U + a,
|
||||
6U * nodes[i] + 3U + b);
|
||||
}
|
||||
}
|
||||
double stiffness = 0.0;
|
||||
{
|
||||
const dense_blas_internal::ScopedLocalDenseThreads local_threads{};
|
||||
stiffness = direction.Dot(metric.Multiply(direction));
|
||||
}
|
||||
if (!std::isfinite(stiffness) || !(stiffness > 0.0)) {
|
||||
return Result<Regularity>::Failure(
|
||||
Failure(domain, "dynamic-algebraic-regularity",
|
||||
@@ -454,22 +518,37 @@ Result<Regularity> CheckRegularity(const Domain& domain,
|
||||
weights[i] = std::sqrt(stiffness);
|
||||
}
|
||||
std::vector<CooContribution> entries;
|
||||
std::vector<double> null_coefficients;
|
||||
for (std::size_t row = 0; row < nodes.size(); ++row) {
|
||||
entries.push_back({row, row, 0.0, 0U, entries.size()});
|
||||
null_coefficients.push_back(0.0);
|
||||
for (std::size_t index = gradient.RowOffsets()[row];
|
||||
index < gradient.RowOffsets()[row + 1U]; ++index) {
|
||||
const std::size_t full = gradient.ColumnIndices()[index];
|
||||
if (full % 6U >= 3U && node_null[full / 6U] != no_null) {
|
||||
const std::size_t column = node_null[full / 6U];
|
||||
entries.push_back(
|
||||
{row, column,
|
||||
gradient.Values()[index] *
|
||||
assembly.rotations[full / 6U].drill_null[full % 6U - 3U] /
|
||||
weights[row] / weights[column],
|
||||
0U, entries.size()});
|
||||
{row, column, gradient.Values()[index], 0U, entries.size()});
|
||||
null_coefficients.push_back(
|
||||
assembly.rotations[full / 6U].drill_null[full % 6U - 3U]);
|
||||
}
|
||||
}
|
||||
}
|
||||
Vector gradient_values{entries.size()};
|
||||
Vector null_values{entries.size()};
|
||||
for (std::size_t i = 0U; i < entries.size(); ++i) {
|
||||
gradient_values[i] = entries[i].value;
|
||||
null_values[i] = null_coefficients[i];
|
||||
}
|
||||
Vector products{0U};
|
||||
{
|
||||
const dense_blas_internal::ScopedLocalDenseThreads local_threads{};
|
||||
products =
|
||||
dense_blas_internal::MultiplyDiagonal(gradient_values, null_values);
|
||||
}
|
||||
for (std::size_t i = 0U; i < entries.size(); ++i)
|
||||
entries[i].value =
|
||||
products[i] / weights[entries[i].row] / weights[entries[i].column];
|
||||
auto matrix = MakeSparse(nodes.size(), nodes.size(), std::move(entries));
|
||||
if (!matrix.HasValue())
|
||||
return Result<Regularity>::Failure(matrix.GetStatus());
|
||||
|
||||
@@ -6,10 +6,12 @@
|
||||
#include <limits>
|
||||
#include <map>
|
||||
#include <sstream>
|
||||
#include <stdexcept>
|
||||
#include <string>
|
||||
#include <utility>
|
||||
|
||||
#include "fesa/solvers/linear/tangent_solver.h"
|
||||
#include "math/dense_blas_internal.h"
|
||||
#include "math/high_low_arithmetic.h"
|
||||
|
||||
namespace fesa::hht_reduced_internal {
|
||||
@@ -614,10 +616,33 @@ Matrix PhysicalJacobian(const ConstraintOperators& operators,
|
||||
|
||||
Vector ContractConstraintHessian(const ConstraintOperators& operators,
|
||||
const Vector& left, const Vector& right) {
|
||||
const dense_blas_internal::ScopedLocalDenseThreads local_threads{};
|
||||
Vector result{operators.rows.size()};
|
||||
for (std::size_t row = 0U; row < operators.rows.size(); ++row)
|
||||
for (const auto& entry : operators.rows[row].hessian)
|
||||
result[row] += entry.value * left[entry.row] * right[entry.column];
|
||||
for (std::size_t row = 0U; row < operators.rows.size(); ++row) {
|
||||
const auto& hessian = operators.rows[row].hessian;
|
||||
Vector coefficients{hessian.size()};
|
||||
Vector left_values{hessian.size()};
|
||||
Vector right_values{hessian.size()};
|
||||
for (std::size_t i = 0U; i < hessian.size(); ++i) {
|
||||
coefficients[i] = hessian[i].value;
|
||||
left_values[i] = left[hessian[i].row];
|
||||
right_values[i] = right[hessian[i].column];
|
||||
}
|
||||
try {
|
||||
const Vector first =
|
||||
dense_blas_internal::MultiplyDiagonal(coefficients, left_values);
|
||||
const Vector products =
|
||||
dense_blas_internal::MultiplyDiagonal(first, right_values);
|
||||
// Retain the original entry order and left-associated products; only
|
||||
// ordinary products move to MKL. This is failure-only replay evidence.
|
||||
for (std::size_t i = 0U; i < products.Size(); ++i)
|
||||
result[row] += products[i];
|
||||
} catch (const std::invalid_argument&) {
|
||||
// A nonfinite input/intermediate cannot yield a finite original sum.
|
||||
// Keep the existing caller's finite failure without a scalar fallback.
|
||||
result[row] = std::numeric_limits<double>::quiet_NaN();
|
||||
}
|
||||
}
|
||||
return result;
|
||||
}
|
||||
|
||||
@@ -1186,13 +1211,19 @@ Result<double> CheckGraphRegularity(
|
||||
Failure("Reduced graph regularity node is invalid.",
|
||||
"dynamic-mass-regularity"));
|
||||
const auto& null = assembly.rotations[node].drill_null;
|
||||
double metric = 0.0;
|
||||
for (std::size_t i = 0U; i < 3U; ++i)
|
||||
Matrix metric_block{3U, 3U};
|
||||
Vector direction{3U};
|
||||
for (std::size_t i = 0U; i < 3U; ++i) {
|
||||
direction[i] = null[i];
|
||||
for (std::size_t j = 0U; j < 3U; ++j)
|
||||
metric += null[i] *
|
||||
SparseEntry(assembly.drilling_metric, 6U * node + 3U + i,
|
||||
6U * node + 3U + j) *
|
||||
null[j];
|
||||
metric_block(i, j) = SparseEntry(
|
||||
assembly.drilling_metric, 6U * node + 3U + i, 6U * node + 3U + j);
|
||||
}
|
||||
double metric = 0.0;
|
||||
{
|
||||
const dense_blas_internal::ScopedLocalDenseThreads local_threads{};
|
||||
metric = direction.Dot(metric_block.Multiply(direction));
|
||||
}
|
||||
if (!std::isfinite(metric) || !(metric > 0.0))
|
||||
return Result<double>::Failure(Failure(
|
||||
"Reduced graph requires a positive finite null drilling metric.",
|
||||
|
||||
@@ -8,6 +8,7 @@
|
||||
#include <utility>
|
||||
|
||||
#include "fesa/model/model_types.h"
|
||||
#include "math/dense_blas_internal.h"
|
||||
|
||||
namespace fesa {
|
||||
|
||||
@@ -223,28 +224,18 @@ Matrix ScaledMatrix(const Matrix& source, double factor) {
|
||||
return result;
|
||||
}
|
||||
|
||||
/// @brief Lifts a local matrix by a deterministic serial congruence product.
|
||||
/// @note The loop and accumulation order are part of reproducible stiffness.
|
||||
/// @brief Lifts a local matrix through MKL and mirrors the upper triangle.
|
||||
Matrix Congruence(const Matrix& local, const Matrix& transformation) {
|
||||
if (local.Rows() != local.Columns() ||
|
||||
local.Rows() != transformation.Rows()) {
|
||||
throw std::invalid_argument{
|
||||
"MITC4 congruence dimensions are incompatible."};
|
||||
}
|
||||
Matrix result{transformation.Columns(), transformation.Columns()};
|
||||
Matrix result = dense_blas_internal::MultiplyTransposeLeft(
|
||||
transformation, local.Multiply(transformation));
|
||||
for (std::size_t row = 0U; row < result.Rows(); ++row) {
|
||||
for (std::size_t column = row; column < result.Columns(); ++column) {
|
||||
double value = 0.0;
|
||||
for (std::size_t local_row = 0U; local_row < local.Rows(); ++local_row) {
|
||||
for (std::size_t local_column = 0U; local_column < local.Columns();
|
||||
++local_column) {
|
||||
value += transformation(local_row, row) *
|
||||
local(local_row, local_column) *
|
||||
transformation(local_column, column);
|
||||
}
|
||||
}
|
||||
result(row, column) = value;
|
||||
result(column, row) = value;
|
||||
result(column, row) = result(row, column);
|
||||
}
|
||||
}
|
||||
return result;
|
||||
@@ -611,7 +602,8 @@ Matrix Mitc4Shell::TransverseShearSectionMatrix() const {
|
||||
return result;
|
||||
}
|
||||
|
||||
Result<Mitc4Stiffness> Mitc4Shell::Stiffness() const {
|
||||
Result<Mitc4Stiffness> Mitc4Shell::Stiffness() const try {
|
||||
const dense_blas_internal::ScopedLocalDenseThreads local_threads{};
|
||||
const Matrix constitutive = MaterialConstitutive5();
|
||||
const Matrix tying_samples = CovariantTyingShearSamples20();
|
||||
Matrix physical_local{kPhysicalDofCount, kPhysicalDofCount};
|
||||
@@ -627,17 +619,12 @@ Result<Mitc4Stiffness> Mitc4Shell::Stiffness() const {
|
||||
const Matrix strain = StrainDisplacement(
|
||||
point.natural_coordinates[0], point.natural_coordinates[1],
|
||||
point.natural_coordinates[2], &tying_samples);
|
||||
const Matrix integrand = dense_blas_internal::MultiplyTransposeLeft(
|
||||
strain, constitutive.Multiply(strain));
|
||||
for (std::size_t row = 0U; row < kPhysicalDofCount; ++row) {
|
||||
for (std::size_t column = row; column < kPhysicalDofCount; ++column) {
|
||||
double integrand = 0.0;
|
||||
for (std::size_t first = 0U; first < 5U; ++first) {
|
||||
for (std::size_t second = 0U; second < 5U; ++second) {
|
||||
integrand += strain(first, row) * constitutive(first, second) *
|
||||
strain(second, column);
|
||||
}
|
||||
}
|
||||
const double contribution =
|
||||
integrand * geometry.jacobian * point.weight;
|
||||
integrand(row, column) * geometry.jacobian * point.weight;
|
||||
physical_local(row, column) += contribution;
|
||||
if (row != column) {
|
||||
physical_local(column, row) += contribution;
|
||||
@@ -714,6 +701,8 @@ Result<Mitc4Stiffness> Mitc4Shell::Stiffness() const {
|
||||
Mitc4Stiffness{std::move(physical_local), std::move(physical_global),
|
||||
std::move(drilling_global), std::move(stabilized_global),
|
||||
drilling_stiffness});
|
||||
} catch (const std::exception& error) {
|
||||
return StiffnessFailure(source_location_, identity_, error.what());
|
||||
}
|
||||
|
||||
Result<Mitc4Mass> Mitc4Shell::Mass(const double density) const {
|
||||
|
||||
@@ -4,11 +4,13 @@
|
||||
#include <array>
|
||||
#include <cmath>
|
||||
#include <cstddef>
|
||||
#include <exception>
|
||||
#include <limits>
|
||||
#include <string>
|
||||
#include <utility>
|
||||
|
||||
#include "fesa/elements/finite_rotation.h"
|
||||
#include "math/dense_blas_internal.h"
|
||||
|
||||
namespace fesa {
|
||||
namespace {
|
||||
@@ -35,6 +37,16 @@ class InertiaSum {
|
||||
double correction_ = 0.0;
|
||||
};
|
||||
|
||||
/// @brief Contracts two nodal 6-by-3 coefficient blocks through dense MKL.
|
||||
/// @note Nonfinite coefficients remain failures of the final inertia gate.
|
||||
void DotBlocks(const std::array<double, 18U>& left,
|
||||
const std::array<double, 18U>& right,
|
||||
std::array<double, 36U>& result) {
|
||||
if (!dense_blas_internal::MultiplyTransposeRight(
|
||||
left.data(), 6U, right.data(), 6U, 3U, result.data()))
|
||||
result.fill(std::numeric_limits<double>::quiet_NaN());
|
||||
}
|
||||
|
||||
Vector3 WeightedSum(const std::array<double, kNodes>& weights,
|
||||
const std::array<Vector3, kNodes>& values) {
|
||||
Vector3 result{};
|
||||
@@ -442,12 +454,11 @@ Status CheckPhysicalMass(const Matrix& mass,
|
||||
}
|
||||
double gram_error = 0.0;
|
||||
double orthogonality_error = 0.0;
|
||||
const Matrix gram =
|
||||
dense_blas_internal::MultiplyTransposeLeft(complement, complement);
|
||||
for (std::size_t row = 0U; row < kPhysical; ++row) {
|
||||
for (std::size_t column = 0U; column < kPhysical; ++column) {
|
||||
double entry = row == column ? -1.0 : 0.0;
|
||||
for (std::size_t inner = 0U; inner < kDofs; ++inner) {
|
||||
entry += complement(inner, row) * complement(inner, column);
|
||||
}
|
||||
const double entry = gram(row, column) - (row == column ? 1.0 : 0.0);
|
||||
gram_error = std::hypot(gram_error, entry);
|
||||
}
|
||||
for (std::size_t node = 0U; node < kNodes; ++node) {
|
||||
@@ -472,55 +483,42 @@ Status CheckPhysicalMass(const Matrix& mass,
|
||||
return fail("invalid-nonlinear-inertia-null",
|
||||
"Scaled mass symmetry and analytic null identities failed.");
|
||||
}
|
||||
Matrix block{kPhysical, kPhysical};
|
||||
Matrix mass_complement{kDofs, kPhysical};
|
||||
for (std::size_t row = 0U; row < kDofs; ++row) {
|
||||
for (std::size_t column = 0U; column < kPhysical; ++column) {
|
||||
for (std::size_t inner = 0U; inner < kDofs; ++inner) {
|
||||
mass_complement(row, column) +=
|
||||
scaled(row, inner) * complement(inner, column);
|
||||
}
|
||||
}
|
||||
}
|
||||
const Matrix mass_complement = scaled.Multiply(complement);
|
||||
const Matrix block =
|
||||
dense_blas_internal::MultiplyTransposeLeft(complement, mass_complement);
|
||||
double block_norm = 0.0;
|
||||
for (std::size_t row = 0U; row < kPhysical; ++row) {
|
||||
double row_sum = 0.0;
|
||||
for (std::size_t column = 0U; column < kPhysical; ++column) {
|
||||
for (std::size_t inner = 0U; inner < kDofs; ++inner) {
|
||||
block(row, column) +=
|
||||
complement(inner, row) * mass_complement(inner, column);
|
||||
}
|
||||
row_sum += std::abs(block(row, column));
|
||||
}
|
||||
block_norm = std::max(block_norm, row_sum);
|
||||
}
|
||||
Matrix lower{kPhysical, kPhysical};
|
||||
for (std::size_t row = 0U; row < kPhysical; ++row) {
|
||||
for (std::size_t column = 0U; column <= row; ++column) {
|
||||
double entry = block(row, column);
|
||||
for (std::size_t inner = 0U; inner < column; ++inner) {
|
||||
entry -= lower(row, inner) * lower(column, inner);
|
||||
}
|
||||
if (!std::isfinite(entry) || (row == column && !(entry > 0.0))) {
|
||||
return fail(
|
||||
"invalid-nonlinear-inertia-positive-mass",
|
||||
"Physical mass requires strictly positive Cholesky pivots.");
|
||||
}
|
||||
lower(row, column) =
|
||||
row == column ? std::sqrt(entry) : entry / lower(column, column);
|
||||
}
|
||||
Matrix inverse_lower{kPhysical, kPhysical};
|
||||
auto factor_failure = dense_blas_internal::CholeskyFailure::kNone;
|
||||
if (!dense_blas_internal::CholeskyLowerAndInverse(block, lower, inverse_lower,
|
||||
&factor_failure)) {
|
||||
if (factor_failure == dense_blas_internal::CholeskyFailure::kInverse)
|
||||
return fail(
|
||||
"ill-conditioned-nonlinear-inertia-positive-mass",
|
||||
"Physical mass reciprocal infinity condition is below 2^-32.");
|
||||
return fail("invalid-nonlinear-inertia-positive-mass",
|
||||
"Physical mass requires strictly positive Cholesky pivots.");
|
||||
}
|
||||
std::array<double, kPhysical> inverse_row_sums{};
|
||||
double reconstruction_error = 0.0;
|
||||
double block_frobenius = 0.0;
|
||||
Matrix transpose{kPhysical, kPhysical};
|
||||
for (std::size_t row = 0U; row < kPhysical; ++row)
|
||||
for (std::size_t column = 0U; column < kPhysical; ++column)
|
||||
transpose(row, column) = lower(column, row);
|
||||
const Matrix reconstructed = lower.Multiply(transpose);
|
||||
for (std::size_t row = 0U; row < kPhysical; ++row) {
|
||||
for (std::size_t column = 0U; column < kPhysical; ++column) {
|
||||
double reconstructed = 0.0;
|
||||
for (std::size_t inner = 0U; inner <= std::min(row, column); ++inner) {
|
||||
reconstructed += lower(row, inner) * lower(column, inner);
|
||||
}
|
||||
reconstruction_error =
|
||||
std::hypot(reconstruction_error, reconstructed - block(row, column));
|
||||
std::hypot(reconstruction_error,
|
||||
reconstructed(row, column) - block(row, column));
|
||||
block_frobenius = std::hypot(block_frobenius, block(row, column));
|
||||
}
|
||||
}
|
||||
@@ -528,25 +526,11 @@ Status CheckPhysicalMass(const Matrix& mass,
|
||||
return fail("invalid-nonlinear-inertia-positive-mass",
|
||||
"Physical mass Cholesky reconstruction failed.");
|
||||
}
|
||||
for (std::size_t column = 0U; column < kPhysical; ++column) {
|
||||
std::array<double, kPhysical> solution{};
|
||||
for (std::size_t row = 0U; row < kPhysical; ++row) {
|
||||
double rhs = row == column ? 1.0 : 0.0;
|
||||
for (std::size_t inner = 0U; inner < row; ++inner) {
|
||||
rhs -= lower(row, inner) * solution[inner];
|
||||
}
|
||||
solution[row] = rhs / lower(row, row);
|
||||
}
|
||||
for (std::size_t reverse = kPhysical; reverse > 0U; --reverse) {
|
||||
const std::size_t row = reverse - 1U;
|
||||
double rhs = solution[row];
|
||||
for (std::size_t inner = row + 1U; inner < kPhysical; ++inner) {
|
||||
rhs -= lower(inner, row) * solution[inner];
|
||||
}
|
||||
solution[row] = rhs / lower(row, row);
|
||||
inverse_row_sums[row] += std::abs(solution[row]);
|
||||
}
|
||||
}
|
||||
const Matrix inverse =
|
||||
dense_blas_internal::MultiplyTransposeLeft(inverse_lower, inverse_lower);
|
||||
for (std::size_t column = 0U; column < kPhysical; ++column)
|
||||
for (std::size_t row = 0U; row < kPhysical; ++row)
|
||||
inverse_row_sums[row] += std::abs(inverse(row, column));
|
||||
const double inverse_norm =
|
||||
*std::max_element(inverse_row_sums.begin(), inverse_row_sums.end());
|
||||
const double reciprocal_condition = 1.0 / block_norm / inverse_norm;
|
||||
@@ -712,6 +696,7 @@ Result<NonlinearMitc4Inertia> NonlinearMitc4Inertia::Create(
|
||||
Result<NonlinearMitc4InertiaEvaluation> NonlinearMitc4Inertia::Evaluate(
|
||||
const NonlinearMitc4TrialDofs& trial, const Vector& velocity,
|
||||
const Vector& acceleration) const {
|
||||
const dense_blas_internal::ScopedLocalDenseThreads local_threads{};
|
||||
if (velocity.Size() != kDofs || acceleration.Size() != kDofs ||
|
||||
!IsFinite(velocity) || !IsFinite(acceleration)) {
|
||||
return Failure<NonlinearMitc4InertiaEvaluation>(
|
||||
@@ -899,6 +884,42 @@ Result<NonlinearMitc4InertiaEvaluation> NonlinearMitc4Inertia::Evaluate(
|
||||
result.momentum_rate_scale += scale * acceleration_point.Norm();
|
||||
result.angular_momentum_rate_scale +=
|
||||
scale * position.Cross(acceleration_point).Norm();
|
||||
std::array<double, 18U> h_block;
|
||||
std::array<double, 18U> velocity_block;
|
||||
std::array<double, 18U> position_block;
|
||||
for (std::size_t local = 0U; local < 6U; ++local) {
|
||||
const auto field = 6U * mass_node + local;
|
||||
for (std::size_t axis = 0U; axis < 3U; ++axis) {
|
||||
h_block[3U * local + axis] = h[field][axis];
|
||||
velocity_block[3U * local + axis] =
|
||||
velocity_derivative[field][axis];
|
||||
position_block[3U * local + axis] =
|
||||
position_derivative[field][axis];
|
||||
}
|
||||
}
|
||||
std::array<double, 36U> mass_block;
|
||||
std::array<double, 36U> velocity_product;
|
||||
std::array<double, 36U> position_product;
|
||||
DotBlocks(h_block, h_block, mass_block);
|
||||
DotBlocks(h_block, velocity_block, velocity_product);
|
||||
DotBlocks(h_block, position_block, position_product);
|
||||
std::array<std::array<double, 36U>, 3U> mass_variation;
|
||||
for (std::size_t direction = 0U; direction < 3U; ++direction) {
|
||||
std::array<double, 18U> derivative_block;
|
||||
for (std::size_t local = 0U; local < 6U; ++local) {
|
||||
const Vector3 derivative =
|
||||
local < 3U ? Vector3{}
|
||||
: z * rotations[mass_node]
|
||||
.director_second[local - 3U][direction];
|
||||
for (std::size_t axis = 0U; axis < 3U; ++axis)
|
||||
derivative_block[3U * local + axis] = derivative[axis];
|
||||
}
|
||||
std::array<double, 36U> reverse;
|
||||
DotBlocks(derivative_block, h_block, mass_variation[direction]);
|
||||
DotBlocks(h_block, derivative_block, reverse);
|
||||
for (std::size_t index = 0U; index < 36U; ++index)
|
||||
mass_variation[direction][index] += reverse[index];
|
||||
}
|
||||
for (std::size_t row = 6U * mass_node; row < 6U * (mass_node + 1U);
|
||||
++row) {
|
||||
// Keep c independent of a; subtracting M*a destroys small c values.
|
||||
@@ -906,10 +927,11 @@ Result<NonlinearMitc4InertiaEvaluation> NonlinearMitc4Inertia::Evaluate(
|
||||
scale * h[row].Dot(convective_point);
|
||||
for (std::size_t column = 6U * mass_node;
|
||||
column < 6U * (mass_node + 1U); ++column) {
|
||||
result.mass(row, column) += scale * h[row].Dot(h[column]);
|
||||
const auto local_index = 6U * (row % 6U) + column % 6U;
|
||||
result.mass(row, column) += scale * mass_block[local_index];
|
||||
result.velocity_tangent(row, column) +=
|
||||
scale * h[row].Dot(velocity_derivative[column]);
|
||||
double position_entry = h[row].Dot(position_derivative[column]);
|
||||
scale * velocity_product[local_index];
|
||||
double position_entry = position_product[local_index];
|
||||
if (row / 6U == column / 6U && row % 6U >= 3U &&
|
||||
column % 6U >= 3U) {
|
||||
const std::size_t node = row / 6U;
|
||||
@@ -922,20 +944,10 @@ Result<NonlinearMitc4InertiaEvaluation> NonlinearMitc4Inertia::Evaluate(
|
||||
result.position_tangent(row, column) += scale * position_entry;
|
||||
if (column % 6U >= 3U) {
|
||||
const auto direction = column % 6U - 3U;
|
||||
const Vector3 dh_row =
|
||||
row % 6U < 3U
|
||||
? Vector3{}
|
||||
: z * rotations[mass_node]
|
||||
.director_second[row % 6U - 3U][direction];
|
||||
for (std::size_t local = 0U; local < 6U; ++local) {
|
||||
const auto field = 6U * mass_node + local;
|
||||
const Vector3 dh_field =
|
||||
local < 3U
|
||||
? Vector3{}
|
||||
: z * rotations[mass_node]
|
||||
.director_second[local - 3U][direction];
|
||||
mass_derivative[mass_node][direction][row % 6U][local] +=
|
||||
scale * (dh_row.Dot(h[field]) + h[row].Dot(dh_field));
|
||||
scale *
|
||||
mass_variation[direction][6U * (row % 6U) + local];
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -1004,8 +1016,15 @@ Result<NonlinearMitc4InertiaEvaluation> NonlinearMitc4Inertia::Evaluate(
|
||||
"invalid-nonlinear-inertia-evaluation", source_location_, identity_,
|
||||
"Nonlinear MITC4 inertia evaluation must remain finite.");
|
||||
}
|
||||
const Status physical_mass = CheckPhysicalMass(result.mass, nulls, length,
|
||||
source_location_, identity_);
|
||||
Status physical_mass = Status::Ok();
|
||||
try {
|
||||
physical_mass = CheckPhysicalMass(result.mass, nulls, length,
|
||||
source_location_, identity_);
|
||||
} catch (const std::exception& error) {
|
||||
return Failure<NonlinearMitc4InertiaEvaluation>(
|
||||
"invalid-nonlinear-inertia-positive-mass", source_location_, identity_,
|
||||
error.what());
|
||||
}
|
||||
if (!physical_mass.IsOk()) {
|
||||
return Result<NonlinearMitc4InertiaEvaluation>::Failure(physical_mass);
|
||||
}
|
||||
|
||||
@@ -10,6 +10,7 @@
|
||||
#include <utility>
|
||||
|
||||
#include "fesa/elements/finite_rotation.h"
|
||||
#include "math/dense_blas_internal.h"
|
||||
|
||||
namespace fesa {
|
||||
namespace {
|
||||
@@ -394,22 +395,63 @@ constexpr std::size_t kHessianSize = kGlobalDofCount * kGlobalDofCount;
|
||||
/// @brief Carries exact first and second trial-coordinate variations.
|
||||
class Hessian {
|
||||
public:
|
||||
Hessian() : values_{std::make_shared<std::array<double, kHessianSize>>()} {}
|
||||
Hessian() = default;
|
||||
|
||||
double& operator[](const std::size_t index) { return (*values_)[index]; }
|
||||
double& operator[](const std::size_t index) { return Data()[index]; }
|
||||
|
||||
const double& operator[](const std::size_t index) const {
|
||||
return (*values_)[index];
|
||||
return Storage()[index];
|
||||
}
|
||||
|
||||
auto begin() const { return values_->begin(); }
|
||||
auto begin() const { return Storage().begin(); }
|
||||
|
||||
auto end() const { return values_->end(); }
|
||||
auto end() const { return Storage().end(); }
|
||||
|
||||
double* Data() {
|
||||
if (!values_) {
|
||||
values_ = std::make_shared<Values>();
|
||||
values_->entries.fill(0.0);
|
||||
}
|
||||
return values_->entries.data();
|
||||
}
|
||||
|
||||
const double* ReadData() const { return Storage().data(); }
|
||||
|
||||
/// @brief Gets fresh output storage without redundant zero initialization.
|
||||
/// @note Only fresh operator results use this pointer; all 576 entries must
|
||||
/// be written before any read or copy of the result.
|
||||
double* OverwriteData() {
|
||||
if (!values_) values_ = std::make_shared<Values>();
|
||||
return values_->entries.data();
|
||||
}
|
||||
|
||||
private:
|
||||
std::shared_ptr<std::array<double, kHessianSize>> values_;
|
||||
struct Values {
|
||||
// User-provided construction leaves entries uninitialized for a complete
|
||||
// output overwrite while make_shared retains the single allocation.
|
||||
Values() noexcept {}
|
||||
std::array<double, kHessianSize> entries;
|
||||
};
|
||||
|
||||
const std::array<double, kHessianSize>& Storage() const {
|
||||
// Constants borrow only this immutable zero. Mutable coefficients retain
|
||||
// the existing shared ownership; no trial-dependent cache is introduced.
|
||||
static const std::array<double, kHessianSize> kZero{};
|
||||
return values_ ? values_->entries : kZero;
|
||||
}
|
||||
|
||||
std::shared_ptr<Values> values_;
|
||||
};
|
||||
|
||||
/// @brief Forms an ordinary derivative outer product without a Matrix copy.
|
||||
/// @note Rejected nonfinite operands propagate to the existing Jet finite gate.
|
||||
void Outer(const std::array<double, kGlobalDofCount>& left,
|
||||
const std::array<double, kGlobalDofCount>& right, double* result) {
|
||||
if (!dense_blas_internal::OuterProduct(left.data(), left.size(), right.data(),
|
||||
right.size(), result))
|
||||
std::fill_n(result, kHessianSize, std::numeric_limits<double>::quiet_NaN());
|
||||
}
|
||||
|
||||
/// @brief Carries exact first and second trial-coordinate variations.
|
||||
struct Jet {
|
||||
double value{};
|
||||
@@ -455,8 +497,11 @@ Jet operator+(const Jet& left, const Jet& right) {
|
||||
result.mixed_second[index] =
|
||||
left.mixed_second[index] + right.mixed_second[index];
|
||||
}
|
||||
const double* left_second = left.second.ReadData();
|
||||
const double* right_second = right.second.ReadData();
|
||||
double* result_second = result.second.OverwriteData();
|
||||
for (std::size_t index = 0U; index < kHessianSize; ++index) {
|
||||
result.second[index] = left.second[index] + right.second[index];
|
||||
result_second[index] = left_second[index] + right_second[index];
|
||||
}
|
||||
return result;
|
||||
}
|
||||
@@ -475,8 +520,11 @@ Jet operator-(const Jet& left, const Jet& right) {
|
||||
result.mixed_second[index] =
|
||||
left.mixed_second[index] - right.mixed_second[index];
|
||||
}
|
||||
const double* left_second = left.second.ReadData();
|
||||
const double* right_second = right.second.ReadData();
|
||||
double* result_second = result.second.OverwriteData();
|
||||
for (std::size_t index = 0U; index < kHessianSize; ++index) {
|
||||
result.second[index] = left.second[index] - right.second[index];
|
||||
result_second[index] = left_second[index] - right_second[index];
|
||||
}
|
||||
return result;
|
||||
}
|
||||
@@ -506,13 +554,18 @@ Jet operator*(const Jet& left, const Jet& right) {
|
||||
2.0 * left.directional_first * right.mixed_first[index] +
|
||||
left.value * right.mixed_second[index];
|
||||
}
|
||||
const double* left_second = left.second.ReadData();
|
||||
const double* right_second = right.second.ReadData();
|
||||
double* result_second = result.second.OverwriteData();
|
||||
Outer(left.first, right.first, result_second);
|
||||
std::array<double, kHessianSize> reverse;
|
||||
Outer(right.first, left.first, reverse.data());
|
||||
for (std::size_t row = 0U; row < kGlobalDofCount; ++row) {
|
||||
for (std::size_t column = 0U; column < kGlobalDofCount; ++column) {
|
||||
const std::size_t index = row * kGlobalDofCount + column;
|
||||
result.second[index] = left.second[index] * right.value +
|
||||
left.first[row] * right.first[column] +
|
||||
left.first[column] * right.first[row] +
|
||||
left.value * right.second[index];
|
||||
result_second[index] = left_second[index] * right.value +
|
||||
result_second[index] + reverse[index] +
|
||||
left.value * right_second[index];
|
||||
}
|
||||
}
|
||||
return result;
|
||||
@@ -529,8 +582,10 @@ Jet operator*(const double scalar, const Jet& value) {
|
||||
result.mixed_first[index] = scalar * value.mixed_first[index];
|
||||
result.mixed_second[index] = scalar * value.mixed_second[index];
|
||||
}
|
||||
const double* value_second = value.second.ReadData();
|
||||
double* result_second = result.second.OverwriteData();
|
||||
for (std::size_t index = 0U; index < kHessianSize; ++index) {
|
||||
result.second[index] = scalar * value.second[index];
|
||||
result_second[index] = scalar * value_second[index];
|
||||
}
|
||||
return result;
|
||||
}
|
||||
@@ -559,11 +614,16 @@ Jet Compose(const Jet& input, const double value, const double first,
|
||||
input.first[index] * input.directional_second) +
|
||||
first * input.mixed_second[index];
|
||||
}
|
||||
std::array<double, kGlobalDofCount> scaled_first{};
|
||||
for (std::size_t row = 0U; row < kGlobalDofCount; ++row)
|
||||
scaled_first[row] = second * input.first[row];
|
||||
const double* input_second = input.second.ReadData();
|
||||
double* result_second = result.second.OverwriteData();
|
||||
Outer(scaled_first, input.first, result_second);
|
||||
for (std::size_t row = 0U; row < kGlobalDofCount; ++row) {
|
||||
for (std::size_t column = 0U; column < kGlobalDofCount; ++column) {
|
||||
const std::size_t index = row * kGlobalDofCount + column;
|
||||
result.second[index] = first * input.second[index] +
|
||||
second * input.first[row] * input.first[column];
|
||||
result_second[index] = first * input_second[index] + result_second[index];
|
||||
}
|
||||
}
|
||||
return result;
|
||||
@@ -613,19 +673,32 @@ Jet Atan2(const Jet& y, const Jet& x) {
|
||||
const double derivative_yx =
|
||||
(y.value * y.value - x.value * x.value) / radius_fourth;
|
||||
const double derivative_xx = 2.0 * x.value * y.value / radius_fourth;
|
||||
std::array<double, kGlobalDofCount> scaled_y{};
|
||||
std::array<double, kGlobalDofCount> scaled_x{};
|
||||
for (std::size_t i = 0U; i < kGlobalDofCount; ++i) {
|
||||
scaled_y[i] = derivative_yy * y.first[i];
|
||||
scaled_x[i] = derivative_xx * x.first[i];
|
||||
}
|
||||
std::array<std::array<double, kHessianSize>, 4U> products;
|
||||
Outer(scaled_y, y.first, products[0U].data());
|
||||
Outer(y.first, x.first, products[1U].data());
|
||||
Outer(x.first, y.first, products[2U].data());
|
||||
Outer(scaled_x, x.first, products[3U].data());
|
||||
for (std::size_t index = 0U; index < kGlobalDofCount; ++index) {
|
||||
result.first[index] =
|
||||
derivative_y * y.first[index] + derivative_x * x.first[index];
|
||||
}
|
||||
const double* y_second = y.second.ReadData();
|
||||
const double* x_second = x.second.ReadData();
|
||||
double* result_second = result.second.OverwriteData();
|
||||
for (std::size_t row = 0U; row < kGlobalDofCount; ++row) {
|
||||
for (std::size_t column = 0U; column < kGlobalDofCount; ++column) {
|
||||
const std::size_t index = row * kGlobalDofCount + column;
|
||||
result.second[index] = derivative_y * y.second[index] +
|
||||
derivative_x * x.second[index] +
|
||||
derivative_yy * y.first[row] * y.first[column] +
|
||||
derivative_yx * (y.first[row] * x.first[column] +
|
||||
x.first[row] * y.first[column]) +
|
||||
derivative_xx * x.first[row] * x.first[column];
|
||||
result_second[index] =
|
||||
derivative_y * y_second[index] + derivative_x * x_second[index] +
|
||||
products[0U][index] +
|
||||
derivative_yx * (products[1U][index] + products[2U][index]) +
|
||||
products[3U][index];
|
||||
}
|
||||
}
|
||||
// Use a bounded ratio for the directional third derivative only. Retain
|
||||
@@ -1181,10 +1254,14 @@ Jet DrillingEnergy(const std::array<Vector3, kNodeCount>& coordinates,
|
||||
DrillSpinRate(trial.rotation[node], initial_directors[node]) * gamma;
|
||||
}
|
||||
energy = energy + 0.5 * drilling_stiffness * gamma * gamma;
|
||||
std::array<double, kGlobalDofCount> scaled_gradient{};
|
||||
for (std::size_t row = 0U; row < kGlobalDofCount; ++row)
|
||||
scaled_gradient[row] = drilling_stiffness * gamma.first[row];
|
||||
std::array<double, kHessianSize> contribution;
|
||||
Outer(scaled_gradient, gamma.first, contribution.data());
|
||||
for (std::size_t row = 0U; row < kGlobalDofCount; ++row) {
|
||||
for (std::size_t column = 0U; column < kGlobalDofCount; ++column) {
|
||||
(*metric)(row, column) +=
|
||||
drilling_stiffness * gamma.first[row] * gamma.first[column];
|
||||
(*metric)(row, column) += contribution[row * kGlobalDofCount + column];
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -1505,6 +1582,7 @@ NonlinearMitc4Shell::EvaluateExternalDrillingConstraint(
|
||||
const std::size_t node, const Vector3& phi, const Vector3& phi_dot,
|
||||
const Vector3& force, const Vector3& force_rate,
|
||||
const Vector3& force_acceleration) const {
|
||||
const dense_blas_internal::ScopedLocalDenseThreads local_threads{};
|
||||
if (node >= kNodeCount || !phi_dot.IsFinite() || !force.IsFinite() ||
|
||||
!force_rate.IsFinite() || !force_acceleration.IsFinite()) {
|
||||
return Failure<NonlinearMitc4ExternalDrillingConstraint>(
|
||||
@@ -1594,6 +1672,9 @@ NonlinearMitc4Shell::EvaluateExternalDrillingConstraint(
|
||||
Result<NonlinearMitc4InternalEquilibrium> EvaluateInternalResidualAndTangent(
|
||||
const NonlinearMitc4Shell& element, const NonlinearMitc4TrialDofs& trial,
|
||||
const Vector* coordinate_direction) {
|
||||
// Element-local MKL work uses one worker only when the caller has no TLS
|
||||
// override. The guard restores that request before returning to global solve.
|
||||
const dense_blas_internal::ScopedLocalDenseThreads local_threads{};
|
||||
if (coordinate_direction != nullptr) {
|
||||
if (coordinate_direction->Size() != kGlobalDofCount) {
|
||||
return Failure<NonlinearMitc4InternalEquilibrium>(
|
||||
|
||||
@@ -1,5 +1,6 @@
|
||||
#include "math/dense_blas_internal.h"
|
||||
|
||||
#include <algorithm>
|
||||
#include <cmath>
|
||||
#include <limits>
|
||||
#include <stdexcept>
|
||||
@@ -26,8 +27,22 @@ ScopedSingleEquationThreads::~ScopedSingleEquationThreads() {
|
||||
if (restore_default_) static_cast<void>(mkl_set_num_threads_local(0));
|
||||
}
|
||||
|
||||
ScopedLocalDenseThreads::ScopedLocalDenseThreads() noexcept {
|
||||
const int previous = mkl_set_num_threads_local(1);
|
||||
if (previous == 0) {
|
||||
restore_default_ = true;
|
||||
} else {
|
||||
static_cast<void>(mkl_set_num_threads_local(previous));
|
||||
}
|
||||
}
|
||||
|
||||
ScopedLocalDenseThreads::~ScopedLocalDenseThreads() {
|
||||
if (restore_default_) static_cast<void>(mkl_set_num_threads_local(0));
|
||||
}
|
||||
|
||||
bool CholeskyLowerAndInverse(const Matrix& matrix, Matrix& lower,
|
||||
Matrix& inverse_lower) {
|
||||
Matrix& inverse_lower, CholeskyFailure* failure) {
|
||||
if (failure != nullptr) *failure = CholeskyFailure::kNone;
|
||||
if (matrix.Rows() != matrix.Columns())
|
||||
throw std::invalid_argument{"Cholesky requires a square matrix."};
|
||||
const auto size = ToMklSize(matrix.Rows());
|
||||
@@ -48,17 +63,30 @@ bool CholeskyLowerAndInverse(const Matrix& matrix, Matrix& lower,
|
||||
values[row * matrix.Columns() + column] = matrix(row, column);
|
||||
}
|
||||
if (LAPACKE_dpotrf(LAPACK_ROW_MAJOR, 'L', size.Value(), values.data(),
|
||||
size.Value()) != 0) return false;
|
||||
size.Value()) != 0) {
|
||||
if (failure != nullptr) *failure = CholeskyFailure::kPivot;
|
||||
return false;
|
||||
}
|
||||
for (std::size_t row = 0; row < matrix.Rows(); ++row)
|
||||
for (std::size_t column = 0; column <= row; ++column)
|
||||
for (std::size_t column = 0; column <= row; ++column) {
|
||||
candidate_lower(row, column) = values[row * matrix.Columns() + column];
|
||||
if (!std::isfinite(candidate_lower(row, column))) {
|
||||
if (failure != nullptr) *failure = CholeskyFailure::kPivot;
|
||||
return false;
|
||||
}
|
||||
}
|
||||
if (LAPACKE_dtrtri(LAPACK_ROW_MAJOR, 'L', 'N', size.Value(), values.data(),
|
||||
size.Value()) != 0) return false;
|
||||
size.Value()) != 0) {
|
||||
if (failure != nullptr) *failure = CholeskyFailure::kInverse;
|
||||
return false;
|
||||
}
|
||||
for (std::size_t row = 0; row < matrix.Rows(); ++row)
|
||||
for (std::size_t column = 0; column <= row; ++column) {
|
||||
const auto value = values[row * matrix.Columns() + column];
|
||||
if (!std::isfinite(candidate_lower(row, column)) || !std::isfinite(value))
|
||||
if (!std::isfinite(value)) {
|
||||
if (failure != nullptr) *failure = CholeskyFailure::kInverse;
|
||||
return false;
|
||||
}
|
||||
candidate_inverse(row, column) = value;
|
||||
}
|
||||
lower = std::move(candidate_lower);
|
||||
@@ -96,6 +124,41 @@ Matrix MultiplyTransposeLeft(const Matrix& left, const Matrix& right) {
|
||||
return transposed.Multiply(right);
|
||||
}
|
||||
|
||||
bool OuterProduct(const double* left, const std::size_t rows,
|
||||
const double* right, const std::size_t columns,
|
||||
double* destination) {
|
||||
return MultiplyTransposeRight(left, rows, right, columns, 1U, destination);
|
||||
}
|
||||
|
||||
bool MultiplyTransposeRight(const double* left, const std::size_t rows,
|
||||
const double* right, const std::size_t columns,
|
||||
const std::size_t inner, double* destination) {
|
||||
const auto m = ToMklSize(rows);
|
||||
const auto n = ToMklSize(columns);
|
||||
const auto k = ToMklSize(inner);
|
||||
const auto maximum = std::numeric_limits<std::size_t>::max() / sizeof(double);
|
||||
if (!m.HasValue() || !n.HasValue() || !k.HasValue() ||
|
||||
(columns != 0U && rows > maximum / columns) ||
|
||||
(inner != 0U && (rows > maximum / inner || columns > maximum / inner)))
|
||||
throw std::length_error{"Dense product dimensions exceed backend limits."};
|
||||
if (rows == 0U || columns == 0U) return true;
|
||||
if (destination == nullptr ||
|
||||
(inner != 0U && (left == nullptr || right == nullptr)))
|
||||
throw std::invalid_argument{"Dense product requires nonnull storage."};
|
||||
if (inner == 0U) {
|
||||
std::fill_n(destination, rows * columns, 0.0);
|
||||
return true;
|
||||
}
|
||||
for (std::size_t i = 0U; i < rows * inner; ++i)
|
||||
if (!std::isfinite(left[i])) return false;
|
||||
for (std::size_t i = 0U; i < columns * inner; ++i)
|
||||
if (!std::isfinite(right[i])) return false;
|
||||
cblas_dgemm(CblasRowMajor, CblasNoTrans, CblasTrans, m.Value(), n.Value(),
|
||||
k.Value(), 1.0, left, k.Value(), right, k.Value(), 0.0,
|
||||
destination, n.Value());
|
||||
return true;
|
||||
}
|
||||
|
||||
Result<MKL_INT> ToMklSize(const std::size_t size) {
|
||||
if (size > static_cast<std::size_t>((std::numeric_limits<MKL_INT>::max)())) {
|
||||
return Result<MKL_INT>::Failure(Status::Failure(
|
||||
|
||||
@@ -26,6 +26,20 @@ class ScopedSingleEquationThreads {
|
||||
bool restore_default_{false};
|
||||
};
|
||||
|
||||
/// @brief Limits element-local dense work under the caller's default policy.
|
||||
/// @note Positive caller TLS overrides are retained. Default requests are
|
||||
/// restored on success and unwind; process-wide settings are never changed.
|
||||
class ScopedLocalDenseThreads {
|
||||
public:
|
||||
ScopedLocalDenseThreads() noexcept;
|
||||
ScopedLocalDenseThreads(const ScopedLocalDenseThreads&) = delete;
|
||||
ScopedLocalDenseThreads& operator=(const ScopedLocalDenseThreads&) = delete;
|
||||
~ScopedLocalDenseThreads();
|
||||
|
||||
private:
|
||||
bool restore_default_{false};
|
||||
};
|
||||
|
||||
/// @brief Converts a dense storage length to the private MKL integer type.
|
||||
/// @return The converted length or an uncategorized overflow failure.
|
||||
Result<MKL_INT> ToMklSize(std::size_t size);
|
||||
@@ -39,13 +53,38 @@ Matrix MultiplyTransposeLeft(const Matrix& left, const Matrix& right);
|
||||
/// @throws std::length_error if the size exceeds the backend integer range.
|
||||
Vector MultiplyDiagonal(const Vector& diagonal, const Vector& rhs);
|
||||
|
||||
/// @brief Writes one row-major outer product through MKL without allocation.
|
||||
/// @note Source arrays and destination must not alias. A nonfinite input
|
||||
/// returns false before writing; finite product overflow remains for the
|
||||
/// owner's gate. A zero dimension accepts null pointers and performs no backend
|
||||
/// call.
|
||||
/// @throws std::invalid_argument for null storage of a nonempty product.
|
||||
/// @throws std::length_error for dimensions outside the backend integer range.
|
||||
bool OuterProduct(const double* left, std::size_t rows, const double* right,
|
||||
std::size_t columns, double* destination);
|
||||
|
||||
/// @brief Writes left times right-transpose to nonaliased contiguous storage.
|
||||
/// @note Inputs are row-major rows-by-inner and columns-by-inner. Nonfinite
|
||||
/// input returns false before writing. Finite output overflow is not hidden.
|
||||
/// Zero output dimensions accept null pointers; inner zero writes exact zeros.
|
||||
/// @throws std::invalid_argument for missing nonempty storage.
|
||||
/// @throws std::length_error for dimension or storage-size overflow.
|
||||
bool MultiplyTransposeRight(const double* left, std::size_t rows,
|
||||
const double* right, std::size_t columns,
|
||||
std::size_t inner, double* destination);
|
||||
|
||||
/// @brief Distinguishes positive-factor failure from inverse failure.
|
||||
enum class CholeskyFailure { kNone, kPivot, kInverse };
|
||||
|
||||
/// @brief Computes a lower Cholesky factor and its inverse with MKL LAPACK.
|
||||
/// @return False for a nonpositive pivot or nonfinite factor/inverse.
|
||||
/// @note Outputs are replaced only after both finite candidates succeed.
|
||||
/// The optional failure output is initialized even when validation throws.
|
||||
/// @throws std::invalid_argument for a nonsquare or nonfinite input.
|
||||
/// @throws std::length_error for a backend size overflow.
|
||||
bool CholeskyLowerAndInverse(const Matrix& matrix, Matrix& lower,
|
||||
Matrix& inverse_lower);
|
||||
Matrix& inverse_lower,
|
||||
CholeskyFailure* failure = nullptr);
|
||||
|
||||
/// @brief Copies contiguous double values through the private BLAS backend.
|
||||
/// @param source Readable storage for size values when size is nonzero.
|
||||
|
||||
@@ -11,6 +11,98 @@
|
||||
namespace fesa::dense_blas_internal {
|
||||
namespace {
|
||||
|
||||
TEST(DenseBlasInternal,
|
||||
OuterProductUsesRectangularStorageAndPreservesRejection) {
|
||||
const std::array<double, 2U> left{2.0, -3.0};
|
||||
const std::array<double, 3U> right{4.0, -5.0, 0.25};
|
||||
std::array<double, 6U> product{};
|
||||
ASSERT_TRUE(OuterProduct(left.data(), left.size(), right.data(), right.size(),
|
||||
product.data()));
|
||||
const std::array<double, 6U> expected{8.0, -10.0, 0.5, -12.0, 15.0, -0.75};
|
||||
EXPECT_EQ(product, expected);
|
||||
const auto accepted = product;
|
||||
const std::array<double, 2U> invalid{
|
||||
1.0, std::numeric_limits<double>::quiet_NaN()};
|
||||
EXPECT_FALSE(OuterProduct(invalid.data(), invalid.size(), right.data(),
|
||||
right.size(), product.data()));
|
||||
EXPECT_EQ(product, accepted);
|
||||
EXPECT_TRUE(OuterProduct(nullptr, 0U, nullptr, 3U, nullptr));
|
||||
EXPECT_TRUE(OuterProduct(nullptr, 2U, nullptr, 0U, nullptr));
|
||||
EXPECT_THROW(OuterProduct(nullptr, 2U, right.data(), 3U, product.data()),
|
||||
std::invalid_argument);
|
||||
const auto too_large =
|
||||
static_cast<std::size_t>((std::numeric_limits<MKL_INT>::max)()) + 1U;
|
||||
EXPECT_THROW(OuterProduct(nullptr, too_large, nullptr, 1U, nullptr),
|
||||
std::length_error);
|
||||
const auto too_many_elements =
|
||||
std::numeric_limits<std::size_t>::max() / sizeof(double) + 1U;
|
||||
EXPECT_THROW(OuterProduct(nullptr, too_many_elements, nullptr, 1U, nullptr),
|
||||
std::length_error);
|
||||
}
|
||||
|
||||
TEST(DenseBlasInternal, LocalDenseScopeRestoresTlsAfterProductsAndUnwind) {
|
||||
const int previous = mkl_set_num_threads_local(0);
|
||||
struct Restore {
|
||||
int previous;
|
||||
~Restore() { static_cast<void>(mkl_set_num_threads_local(previous)); }
|
||||
} restore{previous};
|
||||
const int default_threads = mkl_get_max_threads();
|
||||
const std::array<double, 2U> left{0.0, 2.0};
|
||||
const std::array<double, 2U> right{3.0, 4.0};
|
||||
std::array<double, 4U> product{};
|
||||
product.fill(std::numeric_limits<double>::quiet_NaN());
|
||||
{
|
||||
const ScopedLocalDenseThreads scope{};
|
||||
EXPECT_EQ(mkl_get_max_threads(), 1);
|
||||
EXPECT_TRUE(
|
||||
OuterProduct(left.data(), 2U, right.data(), 2U, product.data()));
|
||||
EXPECT_DOUBLE_EQ(product[0U], 0.0);
|
||||
EXPECT_DOUBLE_EQ(product[3U], 8.0);
|
||||
}
|
||||
EXPECT_EQ(mkl_get_max_threads(), default_threads);
|
||||
EXPECT_EQ(mkl_set_num_threads_local(0), 0);
|
||||
try {
|
||||
const ScopedLocalDenseThreads scope{};
|
||||
OuterProduct(nullptr, 2U, right.data(), 2U, product.data());
|
||||
} catch (const std::invalid_argument&) {
|
||||
}
|
||||
EXPECT_EQ(mkl_set_num_threads_local(0), 0);
|
||||
static_cast<void>(mkl_set_num_threads_local(3));
|
||||
{
|
||||
const ScopedLocalDenseThreads scope{};
|
||||
EXPECT_EQ(mkl_get_max_threads(), 3);
|
||||
}
|
||||
EXPECT_EQ(mkl_get_max_threads(), 3);
|
||||
}
|
||||
|
||||
TEST(DenseBlasInternal, OuterProductLeavesFiniteInputOverflowForOwnerGate) {
|
||||
const std::array<double, 1U> left{std::numeric_limits<double>::max()};
|
||||
const std::array<double, 1U> right{2.0};
|
||||
std::array<double, 1U> product{};
|
||||
EXPECT_TRUE(OuterProduct(left.data(), 1U, right.data(), 1U, product.data()));
|
||||
EXPECT_TRUE(std::isinf(product[0U]));
|
||||
}
|
||||
|
||||
TEST(DenseBlasInternal, TransposeRightProductUsesInnerAndRectangularStrides) {
|
||||
const std::array<double, 6U> left{1, 2, 3, 4, 5, 6};
|
||||
const std::array<double, 12U> right{7, 8, 9, 10, 11, 12,
|
||||
13, 14, 15, 16, 17, 18};
|
||||
std::array<double, 8U> product;
|
||||
ASSERT_TRUE(MultiplyTransposeRight(left.data(), 2U, right.data(), 4U, 3U,
|
||||
product.data()));
|
||||
const std::array<double, 8U> expected{50, 68, 86, 104, 122, 167, 212, 257};
|
||||
EXPECT_EQ(product, expected);
|
||||
EXPECT_TRUE(
|
||||
MultiplyTransposeRight(nullptr, 2U, nullptr, 4U, 0U, product.data()));
|
||||
for (const auto value : product) EXPECT_DOUBLE_EQ(value, 0.0);
|
||||
auto nonfinite = right;
|
||||
nonfinite[8U] = std::numeric_limits<double>::infinity();
|
||||
product.fill(31.0);
|
||||
EXPECT_FALSE(MultiplyTransposeRight(left.data(), 2U, nonfinite.data(), 4U, 3U,
|
||||
product.data()));
|
||||
for (const auto value : product) EXPECT_DOUBLE_EQ(value, 31.0);
|
||||
}
|
||||
|
||||
TEST(DenseBlasInternal, CDup003ConvertsZeroNormalAndOverflowLengths) {
|
||||
const auto zero = ToMklSize(0U);
|
||||
ASSERT_TRUE(zero.HasValue());
|
||||
@@ -115,6 +207,30 @@ TEST(DenseBlasInternal, CholeskyAndInverseMatchKnownFactorsAndKeepFailedOutput)
|
||||
std::invalid_argument);
|
||||
}
|
||||
|
||||
TEST(DenseBlasInternal,
|
||||
CholeskyFailureReasonPreservesCandidatesAndResetsOnReuse) {
|
||||
Matrix matrix{2U, 2U};
|
||||
matrix(0U, 0U) = 4.0;
|
||||
matrix(1U, 1U) = 9.0;
|
||||
Matrix lower{0U, 0U};
|
||||
Matrix inverse{0U, 0U};
|
||||
auto reason = CholeskyFailure::kInverse;
|
||||
ASSERT_TRUE(CholeskyLowerAndInverse(matrix, lower, inverse, &reason));
|
||||
EXPECT_EQ(reason, CholeskyFailure::kNone);
|
||||
matrix(1U, 1U) = -1.0;
|
||||
EXPECT_FALSE(CholeskyLowerAndInverse(matrix, lower, inverse, &reason));
|
||||
EXPECT_EQ(reason, CholeskyFailure::kPivot);
|
||||
EXPECT_DOUBLE_EQ(lower(1U, 1U), 3.0);
|
||||
EXPECT_DOUBLE_EQ(inverse(1U, 1U), 1.0 / 3.0);
|
||||
matrix(1U, 1U) = 9.0;
|
||||
EXPECT_TRUE(CholeskyLowerAndInverse(matrix, lower, inverse, &reason));
|
||||
EXPECT_EQ(reason, CholeskyFailure::kNone);
|
||||
reason = CholeskyFailure::kInverse;
|
||||
EXPECT_THROW(CholeskyLowerAndInverse(Matrix{2U, 1U}, lower, inverse, &reason),
|
||||
std::invalid_argument);
|
||||
EXPECT_EQ(reason, CholeskyFailure::kNone);
|
||||
}
|
||||
|
||||
TEST(DenseBlasInternal, SingleEquationScopeRestoresTlsAndRespectsOverrides) {
|
||||
const int previous = mkl_set_num_threads_local(0);
|
||||
struct Restore {
|
||||
|
||||
Reference in New Issue
Block a user