AI - Software Tools & Optimizations - Page 3#
An Introduction to Primus-Turbo: A Library for Accelerating Transformer Models on AMD GPUs
Primus streamlines training on AMD ROCm, from fine-tuning to massive pretraining on MI300X GPUs—faster, safer, and easier to debug
Efficient LLM Serving with MTP: DeepSeek V3 and SGLang on AMD Instinct GPUs
This blog will show you how to speed up LLM inference with Multi-Token Prediction in DeepSeek V3 & SGLang on AMD Instinct GPUs
GEMM Tuning within hipBLASLt - Part 1
We introduce a hipBLASLt tuning tool that lets developers optimize GEMM problem sizes and integrate them into the library.
Unleashing AMD Instinct™ MI300X GPUs for LLM Serving: Disaggregating Prefill & Decode with SGLang
Learn how prefill–decode disaggregation improves LLM inference by reducing latency, enhancing throughput, and optimizing resource usage.
AITER-Enabled MLA Layer Inference on AMD Instinct MI300X GPUs
AITER boosts DeepSeek-V3’s MLA on AMD MI300X GPUs with low-rank projections, shared KV paths & matrix absorption for 2× faster inference.
Primus: A Lightweight, Unified Training Framework for Large Models on AMD GPUs
Primus streamlines LLM training on AMD GPUs with unified configs, multi-backend support, preflight validation, and structured logging.
Running ComfyUI on AMD Instinct
This blog shows how to deploy ComfyUI on AMD Instinct GPUs. The blog explains what ComfyUI is and how it works.
Running ComfyUI in Windows with ROCm on WSL
Run ComfyUI on Windows with ROCm and WSL to harness Radeon GPU power for local AI tasks like Stable Diffusion—no dual-boot needed
GEAK: Introducing Triton Kernel AI Agent & Evaluation Benchmarks
AMD introduces GEAK, an AI agent for generating optimized Triton GPU kernels, achieving up to 63% accuracy and up to 2.59× speedups on MI300X GPUs.
Avoiding LDS Bank Conflicts on AMD GPUs Using CK-Tile Framework
This blog shows how CK-Tile’s XOR-based swizzle optimizes shared memory access in GEMM kernels on AMD GPUs by eliminating LDS bank conflicts
Chain-of-Thought Guided Visual Reasoning Using Llama 3.2 on a Single AMD Instinct MI300X GPU
Fine-tune Llama 3.2 Vision models on AMD MI300X GPU using Torchtune, achieving 2.3× better accuracy with 11B vs 90B model on chart-based tasks.
vLLM V1 Meets AMD Instinct GPUs: A New Era for LLM Inference Performance
vLLM v1 on AMD ROCm boosts LLM serving with faster TTFT, higher throughput, and optimized multimodal support—ready out of the box.