AI Blogs#
Serving CTR Recommendation Models with Triton Inference Server using the ONNX Runtime Backend
Learn how to deploy AI models on AMD GPUs with Triton Inference Server, now supporting ONNX Runtime and Python backends, and see performance benchmarks.
FlashInfer on ROCm: High‑Throughput Prefill Attention via AITER
FlashInfer is an open-source library for accelerating LLM serving that is now supported by ROCm.
Customizing Kernels with hipBLASLt TensileLite GEMM Tuning - Advanced User Guide
Master hipBLASLt TensileLite Tuning. Learn to build custom kernels that deliver 150%-250% faster GEMM performance on AMD Instinct™ MI300X GPUs
Deploy and Customize AMD Solution Blueprints
Learn how to deploy and customize AMD Solution Blueprints — from default deployment to swapping and reusing AMD Inference Microservices across multiple blueprints.
Reproducing the AMD MLPerf Inference v6.0 Submission Result
Provide instructions to potential customers and partners to verify our MLPerf Inference v6.0 submission result.
AMD Instinct™ GPUs MLPerf Inference v6.0 Submission
In this blog, we share the technical details of how we accomplish the results in our MLPerf Inference v6.0 submission.
Leveraging AMD AI Workbench to Scale LLM Inference for Optimal Resource Utilization
Learn how to use the AMD AI Workbench GUI and AIM Engine CLI capabilities to enable and configure autoscaling for your AI workloads.
Training a Robotic Arm Using MuJoCo and JAX on AMD Hardware with ROCm™
A complete guide to training an RL-based pick-and-lift robotic arm in MuJoCo with JAX, running on AMD hardware via ROCm.
Programming Tensor Descriptors in Composable Kernel (CK)
Learn how to use TensorDescriptor in Composable Kernel (CK) to manage multi-dimensional data layouts and write efficient GPU kernels on AMD GPUs.
Engineering Qwen-VL for Production: Vision Module Architecture and Optimization Practices
Explore how to optimize Qwen-VL for production on AMD Instinct MI308X GPUs with ROCm, from vision module architecture to kernel fusion and deployment.
Accelerating Kimi-K2.5 on AMD Instinct™ MI300X: Optimizing Fused MoE with FlyDSL
Optimize Kimi-K2.5 on AMD MI300X using FlyDSL for fused MoE kernel acceleration. Achieve faster TTFT, TPOT, and throughput with our step-by-step optimization guide.
AMD Device Metrics Exporter v1.4.2: Enhanced Observability, Deeper RAS Insights, and Smarter GPU Telemetry for Modern HPC & AI Clusters
Struggling with GPU bottlenecks? Learn how AMD DME v1.4.2 uncovers power, thermal, and RAS issues with actionable, production-ready telemetry.