Optimizing Attention Decode on AMD MI450 GPUs with Gluon Kernels
Attention Decode on AMD MI450 GPUs: A Gluon Kernel Optimization Guide
I explore how agentic AI workloads shift performance bottlenecks to memory systems during LLM inference. Using the AMD Instinct MI450 GPU, I demonstrate how its new hardware features, like TDM and workgroup clusters, enable high-performance kernel design. By leveraging the Gluon DSL, we achieve 85% of peak HBM bandwidth for attention decode tasks.
As a result, the performance bottleneck shifts from compute units to the memory system.
- touisteur
As much as I enjoy these articles and for AMD to write more light technical articles, it really feels constrained, even strained, to be unable to cite the equivalent terms from the precursor here (NVIDIA). Another batch of jargon for very similar architectures and programming models... HIP and ROCm have actually made amazing strides in making CUDA developers' porting work easy, and I know playing catchup to a (monopolist) moving target you have no power over is bad... but I feel this is part of the thousand paper cuts.
- broadsidepicnic
So when can I buy MI350s for my homelab?