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Rework sparse addM function to support compressed sparse matrices.

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Note:

- M is still a nv x nv uncompressed sparse matrix.
- NNZ precounting still needs to be implemented using the combineSparseCount helper function.

PiperOrigin-RevId: 554452710
Change-Id: I14adf58fc3acd4ed82d864d7c2e9e96ee6b0377d
This commit is contained in:
Kyle Bayes
2023-08-07 06:06:33 -07:00
committed by Copybara-Service
parent 6d7b49ccf5
commit 2d7d5319f7
4 changed files with 93 additions and 104 deletions
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test/benchmark/engine_util_sparse_benchmark_test.cc
+6 -6
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@@ -452,14 +452,14 @@ static void BM_combineSparse(benchmark::State& state, CombineFuncPtr func) {
// compute H = J'*D*J, uncompressed layout
mju_sqrMatTDUncompressedInit(rowadr, m->nv);
mju_sqrMatTDSparse(H, d->efc_J, d->efc_JT, D, d->nefc, m->nv,
rownnz, rowadr, colind,
d->efc_J_rownnz, d->efc_J_rowadr,
d->efc_J_colind, d->efc_J_rowsuper,
d->efc_JT_rownnz, d->efc_JT_rowadr,
d->efc_JT_colind, d->efc_JT_rowsuper, d);
rownnz, rowadr, colind,
d->efc_J_rownnz, d->efc_J_rowadr,
d->efc_J_colind, d->efc_J_rowsuper,
d->efc_JT_rownnz, d->efc_JT_rowadr,
d->efc_JT_colind, d->efc_JT_rowsuper, d);
// compute H = M + J'*D*J
mj_addMSparse(m, d, H, rownnz, rowadr, colind);
mj_addM(m, d, H, rownnz, rowadr, colind);
// time benchmark
for (auto s : state) {