Learning GPU performance engineering through the GPU MODE TriMul challenge - achieving 2.42× speedup on H100 through FP16 optimization, weight fusion, and systematic experimentation.| www.msuiche.com
GPU production constraints are creating infrastructure bottlenecks. Multi-GPU programming, particularly vendor-agnostic implementations, has become essential. In their GPU Mode presentation, AMD Research engineers Muhammad Awad, Muhammad Osama, and Brandon Potter introduced Iris—a Python library that enables fine-grained multi-GPU programming in Triton. Similarly to my previous Gluon blogpost, this post captures my understanding and interpretation of their work, serving as both technical do...| www.msuiche.com