GPU Benchmark Results
- Target profile:
nvidia-gpu
- Suite:
gpu/sparse
- Suite file:
benchmarks/gpu/sparse.yaml
- Timestamp:
2026-10-06T19:36:19.553911+00:00
- tenferro-rs commit:
5cf78c7ec0ad9516dd78bab546d5e7bd42fa3102
GPU Information
- Device:
cuda:0
- Name:
NVIDIA A100 80GB PCIe
- UUID:
GPU-530977e1-4968-9283-4129-9fbec3e66542
- Memory:
80 GiB
- Driver version:
580.126.09
- CUDA version:
13.0
- CUDA runtime:
12.9
- cuDNN version:
92700
CPU Information
- Model:
AMD EPYC 7713P 64-Core Processor
- Vendor:
AuthenticAMD
- Logical CPUs:
64
- Sockets:
1
- Cores per socket:
64
- Threads per core:
1
- NUMA nodes:
1
- Python platform:
Linux-6.8.0-101-generic-x86_64-with-glibc2.39
Median time is reported in milliseconds for ok records.
Inputs are prepared on the GPU before timed runs; initial host-to-device transfer is outside the timed region.
Timed runs include the host API call and backend-native device synchronization. tenferro-rs CUDA uses the explicit tenferro-rs synchronize API without downloading result tensors in the timed region.
Dense and einsum inputs use the same deterministic benchmark generator in the Rust and Python runners; host-to-device layout conversion remains outside the timed region.
tenferro-rs uses native column-major GPU tensors; PyTorch and vendor-wrapper columns use their native row-major framework tensors unless noted.
The cuSOLVER column is torch.linalg with preferred_linalg_library=cusolver; for SVD it pins driver=gesvd as a QR-based cuSOLVER comparison. tenferro-rs CUDA SVD uses its backend default driver policy, currently gesvdj for matrices with both dimensions at most 1024 and gesvd otherwise.
Non-ok cells show the structured backend status.
gpu/sparse / spmm / allocating output
| Problem |
tenferro-rs CUDA trace |
tenferro-rs CUDA eager |
PyTorch CUDA |
cuBLASLt |
CUTLASS |
cuSOLVER |
cuSPARSE |
Ginkgo |
| sparse_synthetic_64k_4m_spmm_f64_rhs1024 |
unsupported |
unsupported |
14.737 |
unsupported |
unsupported |
unsupported |
14.984 |
verification failed |
gpu/sparse / spmv / allocating output
| Problem |
tenferro-rs CUDA trace |
tenferro-rs CUDA eager |
PyTorch CUDA |
cuBLASLt |
CUTLASS |
cuSOLVER |
cuSPARSE |
Ginkgo |
| sparse_synthetic_4m_64m_spmv_f64 |
unsupported |
unsupported |
2.334 |
unsupported |
unsupported |
unsupported |
2.328 |
verification failed |