| Name | Version | Summary | date |
| fbgemm-gpu-genai-nightly |
2025.8.23 |
None |
2025-08-23 14:25:35 |
| fbgemm-gpu-nightly-cpu |
2025.8.23 |
None |
2025-08-23 13:31:16 |
| neurograd |
0.6.9 |
A Pure Python Deep Learning Framework with Automatic Differentiation |
2025-08-23 13:06:30 |
| fbgemm-gpu-genai |
1.3.0 |
None |
2025-08-21 22:23:51 |
| fbgemm-gpu-cpu |
1.3.0 |
None |
2025-08-20 18:58:59 |
| gpu-benchmark-linux |
0.4.4 |
GPU基准测试工具 - 用于评估NVIDIA GPU性能的综合工具包 |
2025-08-19 09:55:09 |
| gpu-benchmark-tool |
0.4.7 |
Multi-vendor GPU health monitoring supporting old GPUs for e-waste reduction |
2025-08-18 22:04:54 |
| img-ops |
0.1.2 |
Device-aware image operations (CPU/GPU/MPS fallback) with a clean Python API for preprocessing tasks. |
2025-08-18 16:38:37 |
| b10-kernel |
0.1.1 |
Baseten Kernel Library |
2025-08-18 15:46:50 |
| feax |
0.0.4 |
A GPU-accelerated finite element analysis framework with JAX. |
2025-08-18 05:47:26 |
| fbgemm-gpu-nightly |
2025.8.17 |
None |
2025-08-17 15:08:03 |
| nvitop-exporter |
1.5.3 |
Prometheus exporter built on top of `nvitop`. |
2025-08-16 06:18:43 |
| nvitop |
1.5.3 |
An interactive NVIDIA-GPU process viewer and beyond, the one-stop solution for GPU process management. |
2025-08-16 06:18:42 |
| torch-lap-cuda |
0.0.3 |
PyTorch wrapper for HyLAC CUDA library for solving linear assignment problems. |
2025-08-14 12:18:30 |
| just-semantic-search-server-cuda |
0.4.3 |
Core interfaces for hybrid search implementations (CUDA version) |
2025-08-11 18:07:36 |
| just-semantic-search-scholar-cuda |
0.4.3 |
Core interfaces for hybrid search implementations (CUDA version) |
2025-08-11 18:07:24 |
| torch-installer-coff33ninja |
1.0.0 |
An intelligent, autonomous PyTorch installer that automatically detects your system, GPU, and CUDA configuration |
2025-08-07 13:35:43 |
| tilus |
0.1 |
Tilus |
2025-08-05 23:09:55 |
| holoscan |
3.5.0 |
The Holoscan SDK: building high-performance AI streaming applications |
2025-08-01 20:29:04 |
| fast-select |
0.2.0 |
A Sci-Kit Learn compatible Numba and CUDA-accelerated implementation of various feature selection algorithms. |
2025-08-01 19:50:45 |