Recent Posts - Page 12#
A Guide to Implementing and Training Generative Pre-trained Transformers (GPT) in JAX on AMD GPUs
A Guide to Implementing and Training Generative Pre-trained Transformers (GPT) in JAX on AMD GPUs
Deep Learning Recommendation Models on AMD GPUs
Deep Learning Recommendation Model on AMD GPU
Mamba on AMD GPUs with ROCm
Best practices of using Mamba on AMD GPUs with ROCm
Fine-tuning and Testing Cutting-Edge Speech Models using ROCm on AMD GPUs
This blog post demonstrates how to fine-tune and test three state-of-the-art machine learning Automatic Speech Recognition (ASR) models, running on AMD GPUs using ROCm.
TensorFlow Profiler in practice: Optimizing TensorFlow models on AMD GPUs
TensorFlow Profiler measures resource use and performance of models, helping identify bottlenecks for optimization. This blog demonstrates the use of the TensorFlow Profiler tool on AMD hardware.
Stone Ridge Expands Reservoir Simulation Options with AMD Instinct™ Accelerators
Stone Ridge Technology (SRT) pioneered the use of GPUs for high performance reservoir simulation (HPC) nearly a decade ago with ECHELON, its flagship software product. ECHELON, the first of its kind, engineered from the outset to harness the full potential of massively parallel GPUs, stands apart in the industry for its power, efficiency, and accuracy. Now, ECHELON has added support for AMDInstinct accelerators into its simulation engine, offering new flexibility and optionality to its clients.
SmoothQuant model inference on AMD Instinct MI300X using Composable Kernel
SmoothQuant model inference on AMD Instinct MI300X using Composable Kernel
Unveiling performance insights with PyTorch Profiler on an AMD GPU
Unveiling Performance Insights with PyTorch Profiler on an AMD GPU
Panoptic segmentation and instance segmentation with Detectron2 on AMD GPUs
Object Detection and Image Segmentation with Detectron2 on AMD GPU
AMD Collaboration with the University of Michigan offers High Performance Open-Source Solutions to the Bioinformatics Community
We are thrilled to share the success story of a 1.5-year collaboration between AMD and the University of Michigan, Ann Arbor where we used the AMD Instinct™ GPUs and ROCm™ software stack to optimize the sequence alignment bottleneck in long read processing workflows.
Siemens taps AMD Instinct™ GPUs to expand high-performance hardware options for Simcenter STAR-CCM+
Siemens recently announced that its Simcenter STAR-CCM+ multi-physics computational fluid dynamics (CFD) software now supports AMD Instinct™ GPUs for GPU-native computation. This move addresses its users' needs for computational efficiency, reduced simulation costs and energy usage, and greater hardware choice.