Software tools & optimizations#
Discover the latest blogs about ROCm software tools, libraries, and performance optimizations to help you get the most out of your AMD hardware.
AMD Instinct MI455X vs MI355X: A Technical Look at the Advancing AI 2026 Inference Numbers
Explore the MI455X vs MI355X inference numbers from Advancing AI 2026, and learn how each benchmark was measured and what it really means.
DI Series: Serving Kimi-K3 MXFP4 Wide-EP Disaggregated on AMD Instinct MI300X and MI325X
Learn how to serve a 1.4 TiB Kimi-K3 MXFP4 mixture-of-experts model disaggregated across AMD Instinct MI300X and MI325X GPUs.
Automating Performance Bottleneck Identification with the TraceLens Agent
TraceLens Agent is an agentic workflow that examines GPU traces to deliver a prioritized optimization report, detailing root causes and fixes.
UltraQuant on AMD Instinct: More Efficient Agentic Serving for Qwen3.8-MXFP4
A native 4-bit MXFP4 KV cache that speeds up Qwen3.8 decode over 8-bit KV on AMD Instinct MI355X, with no accuracy loss.
Debugging Logprob Mismatches in LLM Reinforcement Learning
Learn to debug logprob mismatches between rollout and training with Qwen3 examples on AMD Instinct MI355X GPUs.
Performance Profiling on AMD GPUs - Part 6: Advanced Thread Trace (ATT) - The Microscope for Your Application
Explore rocprofv3 ATT and ROCprof Compute Viewer to trace GPU kernels and explain stalls, waits, and memory-bound performance.
Hyperloom: A Multi-Agent Harness for Autonomous Inference Optimization on AMD GPUs
Hyperloom is a multi-agent harness that autonomously optimizes LLM inference on AMD Instinct GPUs, reaching a median 1.73x throughput gain.
Implementing a High-Performance Custom Diffusion Attention Kernel with FlyDSL
Learn how to implement and optimize flexible, high-performance diffusion attention kernels with FlyDSL.
Thread Trace Part 1: ROCprof Compute Viewer
Learn to capture thread traces with rocprofv3 and analyze instruction timing, stalls, utilization, and counters in ROCprof Compute Viewer.
An Educational GEMM Ladder for Helios GPUs
Build high-performance BF16 GEMM kernels on Helios GPUs with HipKittens, from a naive baseline to optimized schedules.
Iteratively Tuning hipBLASLt TensileLite Kernels: A Smaller Search, a Faster Kernel
Learn why a small iterative search beats a big one-shot sweep for hipBLASLt TensileLite kernels, in less time and with no risk of regression.
veRL on AMD: Production-Ready RL Post-Training on ROCm
Run veRL RL post-training on AMD Instinct GPUs with a turnkey ROCm container, AITER-accelerated rollout, and validated accuracy on MI300 and MI355.