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Removed temporary test files and benchmarks created for omatcopy RVV optimization validation:
- Removed benchmark scripts and result files
- Removed test executables (scalar vs RVV comparison)
- Removed temporary test source files
Previous testing on sg2044 showed RVV implementation achieved ~30% performance improvement
over scalar version for 3000x4000 matrix operations (0.384s vs 0.552s per iteration).
Co-authored-by: gong-flying <gongxiaofei24@iscas.ac.cn>
- Fixed matrix initialization to use row-major order
- Fixed memory allocation size calculation for output matrix
- Optimized RVV simulation with 4-way loop unrolling
- All test cases now pass correctness verification
- Performance improvements: up to 1.26x speedup for alpha=1.0 case
Co-authored-by: gong-flying <gongxiaofei24@iscas.ac.cn>
- Created comprehensive performance test for omatcopy_ct function
- Added RVV vectorized implementation with conditional compilation
- Included build script for SG2044 server testing
- Support both scalar and RVV optimized versions
- Added throughput measurement and detailed performance metrics
Co-authored-by: gong-flying <gongxiaofei24@iscas.ac.cn>
There were a couple of issues with the detection code used to check
for RVV 1.0 on kernels that do not support hwprobe.
1. The vtype clobber was missing
2. The wrong form of vsetvli was being used. The vsetvli x0, x0 form
is inappropriate for this use case as it can only be safely used
in code where the value of vtype is known. The use of vsetvli
x0, x0 here can lead to a failure to detect RVV 1.0, if,
for example, the vill bit happens to be set before
detect_riscv64_rvv100 is called.
We fix both issues by adding the missing clobber and replacing the
first parameter to vsetvli with t0 (which we add to our clobbers).
The compiler options that enable 16 bit floating point instructions
should not be enabled by default when building the RISCV64_ZVL128B
and RISCV64_ZVL256B targets. The zfh and zvfh extensions are not part
of the 'V' extension and are not required by any of the RVA profiles.
There's no guarantee that kernels built with zfh and zvfh will work
correctly on fully compliant RVA23U64 devices.
To fix the issue we only build the RISCV64_ZVL128B and RISCV64_ZVL256B
kernels with the half float flags if BUILD_HFLOAT16=1. We also update
the RISC-V dynamic detection code to disable the RISCV64_ZVL128B and
RISCV64_ZVL256B kernels at runtime if we've built with DYNAMIC_ARCH=1
and BUILD_HFLOAT16=1 and are running on a device that does not support
both Zfh and Zvfh.
Fixes: https://github.com/OpenMathLib/OpenBLAS/issues/5428
1.Verify correctness using BLAS-Tester
2.Using the built-in benchmark to verify performance, the performance of float and doule type improved by about 60% and about 40% respectively.The test command is:
export OMP_NUM_THREADS=1;numactl -C 10 -l ./sgemv.goto 3000 4000 100
export OMP_NUM_THREADS=1;numactl -C 10 -l ./dgemv.goto 3000 4000 100
Martin Kroeker