Vish Vadlamani#
Vish Vadlamani is a Senior Director of Software Engineering at AMD. He and his team are responsible for all AI SDK Vertical, Horizontal and Ecosystem components. He has passion in the AI and cloud computing space with over 3 decades of software development and management experience. Vish did his management coursework from Harvard, Masters in Engineering from UT Austin and a B.Tech in Engineering from IIT Bombay.
Posts by Vish Vadlamani
Bringing the MONAI Model Zoo to AMD Instinct™ GPUs: Validated Inference on ROCm
Learn how to run validated inference for five MONAI Model Zoo bundles on AMD Instinct™ GPUs using a ROCm overlay.
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.
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.
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
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.
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.
Verl 0.9.0 on ROCm™ 10.0: Next-Generation RL Post-Training on AMD Instinct™ GPUs
Enable Verl 0.9.0 on ROCm™ 10. Native AMD platform support, vLLM 0.27 and SGLang in one image, and updated async GRPO/DAPO recipes on AMD Instinct™ GPUs.
Exploring XGBoost: A Deep Dive
A single source explanation of XGBoost features and its working principles.
Scaling RL with verl on AMD Instinct MI355X: Async Walkthrough and Sync Benchmark
Scale RLHF on AMD Instinct MI355X with verl's fully async trainer. Hands-on GRPO + DAPO examples.
From Vector Search to Agentic RAG: Building an Enterprise Research Analyst with hipVS
Learn how to build an agentic RAG research assistant using hipVS GPU-accelerated vector search on AMD Instinct GPUs, with multi-query decomposition, parallel retrieval, and cited sources synthesis.
Accelerating ComfyUI Workflows on AMD Instinct™ MI355X GPUs with ROCm
We show that the MI355X delivers better performance than the B200 for ComfyUI after enabling PyTorch attention for gfx950.
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.
Exploring Use Cases for Scalable AI: Implementing Ray with ROCm 7 Support for Efficient ML Workflows
Ray with ROCm helps you scale AI applications for training and inference workloads on AMD GPUs.
Elevate Your LLM Inference: Autoscaling with Ray, ROCm 7.0.0, and SkyPilot
Learn how to use multi-node and multi-cluster autoscaling in the Ray framework on ROCm 7.0.0 with SkyPilot
Reinforcement Learning from Human Feedback on AMD GPUs with verl and ROCm 7.0.0
Deploy verl on AMD GPUs for fast, scalable RLHF training with ROCm optimization, Docker scripts, and strong throughput and convergence results
Accelerating llama.cpp on AMD Instinct MI300X
Learn more about the superior performance of llama.cpp on Instinct platforms.
DGL in Depth: SE(3)-Transformer on ROCm 7
Inform the AI community about running SE(3)-Transformer with DGL on AMD Instinct platforms.
Modernizing Taichi Lang to LLVM 20 for MI355X GPU Acceleration
Power your next AI application or graphics simulation with high-performance GPU/CPU computing in Python with Taichi Lang.
Accelerating Vector Search: hipVS and hipRAFT on AMD
Learn how hipVS accelerates vector search on AMD Instinct GPUs, with notebook demos for semantic search, RAG, and recommendation systems.
Announcing MONAI 1.0.0 for AMD ROCm: Breakthrough AI Acceleration for Medical Imaging Models on AMD Instinct™ GPUs
Learn how to use Medical Open Network for Artificial Intelligence (MONAI) 1.0 on ROCm, with examples and demonstrations.
Elevating 3D Scene Rendering with GSplat
ROCm Port of GSplat - GPU accelerated rasterization of Gaussian splatting
From Ingestion to Inference: RAG Pipelines on AMD GPUs
Build a RAG enhanced GenAI application that improves the quality of model responses by incorporating data that is missing in the model training data.
Enabling FlashInfer on ROCm for Accelerated LLM Serving
FlashInfer is an open-source library for accelerating LLM serving that is now supported by ROCm.
Coding Agents on AMD GPUs: Fast LLM Pipelines for Developers
Accelerate AI-assisted coding with agentic workflows on AMD GPUs. Deploy DeepSeek-V3.1 via SGLang, vLLM, or llama.cpp to power fast, scalable coding agents
Exploring Use Cases for Scalable AI: Implementing Ray with ROCm Support for Efficient ML Workflows
Ray, combined with ROCm, provides a powerful platform for scaling AI applications, particularly for training and inference workloads.
Llama.cpp Meets Instinct: A New Era of Open-Source AI Acceleration
performance optimizations for llama.cpp on AMD Instinct GPUs
DGL in the Real World: Running GNNs on Real Use Cases
We walk through four advanced GNN workloads from heterogeneous e-commerce graphs to neuroscience applications that we successfully ran using our DGL implementation.
Accelerating Parallel Programming in Python with Taichi Lang on AMD GPUs
This blog provides a how-to guide on installing and programming with Taichi Lang on AMD Instinct GPUs.
Graph Neural Networks at Scale: DGL with ROCm on AMD Hardware
Accelerate Graph Deep Learning on AMD GPUs with DGL and ROCm—scale efficiently with open tools and optimized performance.
Reinforcement Learning from Human Feedback on AMD GPUs with verl and ROCm Integration
Deploy verl on AMD GPUs for fast, scalable RLHF training with ROCm optimization, Docker scripts, and impressive throughput-convergence results
Efficient MoE training on AMD ROCm: How-to use MegaBlocks on AMD GPUs
Learn how to use MegaBlocks to pre-train GPT2 Mixture of Experts (MoE) model, helping you scale your deep learning models effectiveness on AMD GPUs using ROCm
Triton Inference Server with vLLM on AMD GPUs
This blog provides a how-to guide on setting up a Triton Inference Server with vLLM backend powered by AMD GPUs, showcasing robust performance with several LLMs