1 个仓库
Awesome GitHub RepositoriesParallel Kernel Module Loaders
Configures the number of worker threads that compile and load GPU kernel modules concurrently to reduce startup time.
Distinct from Module Loading Systems: Distinct from Module Loading Systems: focuses on parallel compilation and loading of GPU kernel modules, not shell module loading.
Explore 1 awesome GitHub repository matching development tools & productivity · Parallel Kernel Module Loaders. Refine with filters or upvote what's useful.
Awesome Parallel Kernel Module Loaders GitHub Repositories
用 AI 发现最棒的仓库。我们将通过 AI 为您搜索最匹配的仓库。
- nvidia/warp
NVIDIA/warp
6,233在 GitHub 上查看Warp is a Python framework that JIT-compiles Python functions into CUDA kernels for GPU-accelerated parallel computation, with built-in automatic differentiation and multi-framework array interoperability. At its core, it provides a GPU kernel compilation system that enables writing and executing custom GPU kernels directly from Python, while supporting automatic gradient computation through those kernels for integration with machine learning pipelines. The framework also includes tile-based cooperative computing, where thread blocks partition into tiles for shared-memory and tensor-core opera
Sets the number of worker threads that compile and load kernel modules concurrently, reducing startup time on multi-core systems.
Pythoncudadifferentiable-programminggpu
