Combine sparse vectors in-place by first counting total `nnz` and then working backwards from the end. This removes the need for temporary buffers in `mju_combineSparse` and its callers and speeds up the function by ~10%.
PiperOrigin-RevId: 902530210
Change-Id: I4f48c327103552ab968d3915399c6067367bec9f
The BM_CompileManyTextures benchmark temporarily sets the MuJoCo cache capacity to 0. This change ensures that the original cache capacity is restored after the benchmark completes, preventing side effects on other tests.
PiperOrigin-RevId: 864332653
Change-Id: I5f756e30d4922d5e6f9b70d19ba9d0e31cde9259
The new symbolic function is a generalization of the function it replaces. In this CL it takes two unused temp arrays. The actual change in behavior happens in the followup.
New benchmark test output below ("L" is 2 humanoids and 100 free objects, "XL" is 100 humanoids). Note that `symbolic` is only ever called once per Newton iteration, while `numeric` is sometimes called multiple times (when the rank-1 update fails), hence timing them separately is valuable.
```
Benchmark Time(ns) CPU(ns) Iterations
--------------------------------------------------------------
BM_old_L_mean 84382 84703 19547 11.807k items/s
BM_symbolic_L_mean 16345 16381 88414 61.055k items/s
BM_numeric_L_mean 10986 10994 120000 90.999k items/s
BM_old_XL_mean 1241208 1244212 1200 803.924 items/s
BM_symbolic_XL_mean 130917 131042 12720 7.631k items/s
BM_numeric_XL_mean 77004 76767 21116 13.029k items/s
```
PiperOrigin-RevId: 846704054
Change-Id: Ib0c365724d63bf2b81606ca5353756a6496c3a26
This is a no-op "prefactor" of `mj_crb` to reduce the number of lines changed in the upcoming sleeping CL. The main change here is that `mj_crb` now avoids accessing the model and data pointer repeatedly, but instead has the input and output pointers explicitly declared as local variables. A benchmark test found a healthy **14% perf bump** due to two changes:
- Adding `restrict` to `mju_mulInertVec`
- The function-local pointers.
Adding `restrict` to the local pointers had no effect. Note that `mj_crb` is not a particularly expensive function so these speed bumps are not significant per se, but rather indicative of possible future gains with these techniques.
```
Benchmark Time(ns) CPU(ns) Iterations
---------------------------------------------------------------
ORGINAL BASELINE
BM_CRB_BASELINE_mean 4325 4348 993200 230.052k items/s
BASELINE + RESTRICT
BM_CRB_BASELINE_mean 4057 4090 1186150 244.573k items/s
LOCAL POINTERS + RESTRICT
BM_CRB_mean 3772 3800 1001750 263.209k items/s
```
PiperOrigin-RevId: 815798225
Change-Id: Iffdf57b544e8e10562807c617f73ca4ccd1c614f
All instances of mujoco_test in the code base were followed by
a call to target_link_libraries(<testname> fixture gmock).
As anyhow mujoco_test already was calling target_link_libraries
to some predefined list of targets (mujoco and gtest_main),
this PR adds to the list of default linked targets also fixture
and gmock, to reduce the boilerplate.
Furthermore, to completly remove the need for calling
target_link_libraries after a call to mujoco_test, this PR also
add to the mujoco_test macro the ADDITIONAL_LINK_LIBRARIES
argument, that can be used if a given test needs to link some
additional targets beside the default ones.
To permit to use these new features also for mujoco benchmarks,
this PR adds a MAIN_TARGET parameter to mujoco_test, to select
if gtest_main or another target is used to provide the main
entry point to the test executable.
- Modify parse_benchmark_test to not time the first instance of file loading.
- Improve readability of step_benchmark_test.
PiperOrigin-RevId: 680953562
Change-Id: I4569d1b946ecb49b6590ea313f0b598ffc897888
Kyle Bayes