Posts by Chunhung Wang
Day 0 Developer Guide: hipBLASLt Offline GEMM Tuning Script
- 05 November 2025
This blog post focuses on optimizing the performance of a real model using the QuickTune script, illustrated with an example of offline GEMM tuning for the Qwen model on an AMD MI308 GPU. Developed by the AMD Quark Team, the QuickTune script delivers significant GEMM performance improvements with minimal time overhead. QuickTune is an advanced tool for hipBLASLt offline GEMM tuning. It allows users to complete offline tuning with one click, instead of using hipblaslt-bench to tune the model manually.
Avoiding LDS Bank Conflicts on AMD GPUs Using CK-Tile Framework
- 25 July 2025
LDS bank conflict is a common performance bottleneck in GPU kernel development. Composable Kernel (CK-Tile), a kernel development framework for AMD GPUs, provides a framework-level solution for LDS bank conflicts. Composable Kernel for ROCm is used to build portable high-performance kernels for accelerating computing, e.g. HPC, DL and LLMs for training and inference workloads. In this blog, we show you how to analyze, detect, and eliminate LDS bank conflicts using CK-Tile, AMD’s composable GPU kernel framework. A GEMM kernel serves as a classic example for analyzing how threads interact with LDS during both reads and writes. Starting with a naïve memory layout, we evaluate bank conflict behavior, explore mitigation techniques such as padding, and ultimately demonstrate how an XOR-based swizzle transformation achieves a bank conflict-free design.