Featured Posts
ROCm 10.1: Breaking the Data-Movement Bottleneck
ROCm 10.1 targets the data-movement bottleneck with AMD Infinity Storage, NUMA-aware memory, and a modernized stack.
Technical Dive into AMD MLPerf Inference v6.1 Submission
Learn about the ROCm optimizations powering dlrm-v3, llama2-70b, and gpt-oss-120b performance.
A Deep Dive into LDS Optimizations on AMD Instinct MI450 GPUs
Learn how to optimize LDS traffic in Gluon kernels on AMD Instinct MI450 GPUs using transposed loads and partition-conflict-free layouts.
ROCm 10.0: A Decade of Open Compute, Built for the Age of Agentic AI
Explore what's new in ROCm 10.0, headlined by ROCm.AI, the ROCm CLI, AMD Skills, and Hyperloom, alongside the ROCm Core SDK and platform-wide improvements
Two Waves, One Stage Apart: Warp-Pipelining Triton GEMMs on AMD Instinct
Use warp-pipelining to overlap matrix work and data preparation in compute-bound Triton GEMMs on AMD Instinct GPUs.
ROCm 10.0.0 Support for Ray 2.58.0: Enabling Scalable AI Workflows
ROCm 10.0.0 with Ray 2.58.0 continues PyTorch 2.12 and vLLM support.
Training EAGLE3 Speculative Decoding Draft Models on AMD Instinct MI350X with AMD Quark
Learn how the AMD Quark team trains EAGLE3.1 draft models from scratch on AMD Instinct MI350X GPUs using ROCm, vLLM, TorchSpec, and SPEED-Bench.
Group-GEMM in XLA: Making Mixture-of-Experts Fast and Memory-Efficient
Learn how to make JAX/MaxText MoE training more efficient with two new OpenXLA Group-GEMM backends for ragged-dot: ROCm hipBLASLt and generic Triton.
Accelerating MONAI Digital-Pathology Pipelines on AMD Instinct™ GPUs with hipCIM
In this blog you will measure a MONAI digital-pathology pipeline on AMD Instinct™ GPUs using hipCIM as the WSIReader backend.
Micro-World 2: Streaming Real-time Interactive World Model
This blog demonstrates how Micro-World 2 combines precisely annotated action data, four-step diffusion distillation, and ROCm-optimized inference to deliver controllable, long-horizon, real-time world generation on a single AMD Instinct GPU through a fully open-source pipeline.
Optimizing World Action Models on AMD GPUs
Speed up World Action Models on AMD GPUs with GEAK kernels, fewer denoising steps, and latent actions, cutting FastWAM latency 25× at about 97 percent success.
Introducing rocOpt: GPU-Accelerated Decision Optimization on AMD ROCm
Run large-scale MILP, LP, QP, and vehicle routing problems on AMD Instinct GPUs - introducing rocopt, optimization built for ROCm.
FP8 GEMM Optimization on AMD RDNA™ 4 Architecture
Learn how to port an FP16 GEMM kernel to FP8 on AMD RDNA 4 and use the smaller element size to unlock larger tiles and deeper K slices.
Scaling 3D Gaussian Splatting with Distributed Compute: Why One GPU Is Never Enough
Learn how to scale 3D Gaussian splatting across GPUs with distributed training, RCCL, and real-world optimization tips for AMD Instinct GPUs
MoE Training Optimization with Primus
Learn how to speed up MoE training on AMD Instinct GPUs with Primus: a fused MoE megakernel, FP8/MXFP8 expert GEMMs, and training-at-scale tuning.
hipCIM 26.06: GPU-Accelerated Whole-Slide Image I/O on AMD Instinct™ GPUs
In this blog you will see how hipCIM 26.06 reads whole-slide images on AMD Instinct™ GPUs, and how fast and faithfully it decodes them.
Ultralytics YOLO on AMD GPUs: Train, Run, and Deploy with ROCm™
Learn how to train, run, and deploy Ultralytics YOLO26 models on AMD GPUs with PyTorch on ROCm and MIGraphX, starting with Ultralytics 8.4.171.
Enabling Physical AI Agents with Lemonade
Learn to deploy local agents for interactive robot arm manipulation using the Lemonade framework.
AUP Learning Cloud: Streamlining AI Education on AMD
An all-in-one ROCm JupyterHub platform that deploys GPU-ready AI teaching environments on AMD hardware with one installer and open-source teaching labs.
Introducing AMD CDNA™ 5 and the AMD Helios™ Rackscale Solution
Introducing AMD CDNA 5, the AMD Instinct MI455X GPU, and the AMD Helios rackscale solution: an open, integrated platform for rack-scale AI.
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