Meet mKernel: A Multi-GPU, Multi-Node Fused Kernel Library for GPU-Driven Communication
Quick Answer
UC Berkeley's UCCL team has launched mKernel, a unified CUDA kernel that integrates intra-node NVLink, inter-node RDMA, and dense computing.
Quick Take
UC Berkeley's UCCL team has launched mKernel, a unified CUDA kernel that integrates intra-node NVLink, inter-node RDMA, and dense computing. This library aims to enhance GPU-driven communication across multiple GPUs and nodes, streamlining performance and efficiency for complex computational tasks.
Key Points
- mKernel fuses NVLink and RDMA for improved GPU communication.
- The library supports multi-GPU and multi-node configurations.
- Designed to enhance performance in dense computational tasks.
- Developed by UC Berkeley's UCCL team.
Article Excerpt
From source RSS / original summaryUC Berkeley's UCCL team releases mKernel, fusing intra-node NVLink, inter-node RDMA, and dense compute into a single persistent CUDA kernel. The post Meet mKernel: A Multi-GPU, Multi-Node Fused Kernel Library for GPU-Driven Communication appeared first on MarkTechPost.
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