George Wang#
George Wang is Director of AI Software Product Engineering in the AI Group at AMD, where he leads a talented team for AI software solutions, product management, and end-to-end performance optimizations across Data Center, Client, and Edge/Endpoint applications, driving cutting-edge AI capabilities for AMD’s customers, developers, and the broader community.
George with over 20 years of experience in the technology industry, and he holds master’s degree from UESTC.
Posts by George Wang
Kimi-K2-Instruct: Enhanced Out-of-the-Box Performance on AMD Instinct MI355 Series GPUs
Learn how AMD Instinct MI355 Series GPUs deliver competitive Kimi-K2 inference with faster TTFT, lower latency, and strong throughput.
Optimizing FP4 Mixed-Precision Inference with Petit on AMD Instinct MI250 and MI300 GPUs: A Developer’s Perspective
Learn how FP4 mixed-precision on AMD GPUs boosts inference speed and integrates seamlessly with SGLang.
Step-3 Deployment Simplified: A Day 0 Developer’s Guide on AMD Instinct™ GPUs
Learn how to deploy Step-3, a 321B-parameter VLM with MFA & AFD, on AMD Instinct™ GPUs to cut decoding costs and boost long-context reasoning
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.
Day 0 Developer Guide: Running the Latest Open Models from OpenAI on AMD AI Hardware
Day 0 support across our AI hardware ecosystem from our flagship AMD InstinctTM MI355X and MI300X GPUs, AMD Radeon™ AI PRO R700 GPUs and AMD Ryzen™ AI Processors
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
Vibe Coding Pac-Man Inspired Game with DeepSeek-R1 and AMD Instinct MI300X
Learn LLM-powered game dev using DeepSeek-R1 on AMD MI300X GPUs with iterative prompting, procedural generation, and VS Code AI tools
Fine-Tuning LLMs with GRPO on AMD MI300X: Scalable RLHF with Hugging Face TRL and ROCm
Fine-tune LLMs with GRPO on AMD MI300X—leverage ROCm, Hugging Face TRL, and vLLM for efficient reasoning and scalable RLHF
From Theory to Kernel: Implement FlashAttention-v2 with CK-Tile
Learn how to implement FlashAttention-v2 with CK-Tile: minimize memory overhead, maximize compute efficiency, and scale on AMD GPUs
Accelerate DeepSeek-R1 Inference: Integrate AITER into SGLang
Boost DeepSeek-R1 with AITER: Step-by-step SGLang integration for high-performance MoE, GEMM, and attention ops on AMD GPUs
Step-Video-T2V Inference with xDiT on AMD Instinct MI300X GPUs
Learn how to accelerate text-to-video generation using Step-Video-T2V, a 30B parameter T2V model, on AMD MI300X GPUs with ROCm—enabling scalable, high-fidelity video generation from text
Unleash Full GPU Potential: Overlap Communication and Computation with Triton-Distributed
Unlock the full power of AMD GPUs—write portable, efficient kernels with Triton-Distributed, overlapping computation and communication with ease and flexibility
Hands-On with CK-Tile: Develop and Run Optimized GEMM on AMD GPUs
Build high-performance GEMM kernels using CK-Tile on AMD Instinct GPUs with vendor-optimized pipelines and policies for AI and HPC workloads
Unlock Peak Performance on AMD GPUs with Triton Kernel Optimizations
Learn how Triton compiles and optimizes AI kernels on AMD GPUs, with deep dives into IR flows, hardware-specific passes, and performance tuning tips
GEMM Kernel Optimization For AMD GPUs
Guide to how GEMMs can be tuned for optimal performance of AI models on AMD GPUs