PyTorch Researchers Introduce an Optimized Triton FP8 GEMM (General Matrix-Matrix Multiply) Kernel TK-GEMM that Leverages SplitK Parallelization

PyTorch has introduced TK-GEMM, an optimized Triton FP8 GEMM kernel, to speed up FP8 inference for large language models like Llama3 using Triton Kernels. This helps improve performance for Llama3-70B inference problem sizes on Nvidia H100 GPUs, resulting in significant speedups over base Triton GEMM and cuBLAS FP8 and FP16. Additionally, it enhances end-to-end speedup with CUDA graphs. Practical AI Solution Spotlight: Explore the AI Sales Bot from itinai.com/aisalesbot, designed to automate customer engagement 24/7 and manage interactions across all customer journey stages. Discover how AI can redefine your sales processes and customer engagement. Get free consultation at AI Lab in Telegram @itinai and follow @itinaicom on Twitter for more updates.