Recent Posts - Page 37#
Seismic stencil codes - part 1
Seismic Stencil Codes - Part 1: Seismic workloads in the HPC space have a long history of being powered by high-order finite difference methods on structured grids. This trend continues to this day.
Seismic stencil codes - part 3
Seismic Stencil Codes - Part 3: In the last two blog posts, we developed a HIP kernel capable of computing high order finite differences commonly needed in seismic wave propagation.
Benchmarking Machine Learning using ROCm and AMD GPUs: Reproducing Our MLPerf Inference Submission
Benchmarking Machine Learning using ROCm and AMD GPUs: Reproducing Our MLPerf Inference Submission
Performing natural language processing tasks with LLMs on ROCm running on AMD GPUs
Performing natural language processing tasks with LLMs on ROCm running on AMD GPUs
Using AMD GPUs for Enhanced Time Series Forecasting with Transformers
Time series forecasting (TSF) predicts future behavior using past data. This guide focuses on implementing Transformers for TSF, covering preprocessing to evaluation using AMD hardware.
Inferencing with Grok-1 on AMD GPUs
We demonstrate that the massive Grok-1 Model from xAI can run seamlessly on the AMD MI300X GPU accelerator by leveraging the ROCm software platform.
Optimizing RoBERTa: Fine-Tuning with Mixed Precision on AMD
In this blog we explore how to fine-tune the Robustly Optimized BERT Pretraining Approach RoBERTa large language model, with emphasis on PyTorch's mixed precision capabilities. Specifically, we explore using AMD GPUs for mixed precision fine-tuning to achieve faster model training without any major impacts on accuracy.
Using statistical methods to reliably compare algorithm performance in large generative AI models with JAX Profiler on AMD GPUs
Using Statistical Methods to Reliably Compare Algorithm Performance in Large Generative AI Models with JAX Profiler on AMD GPUs
Accelerate PyTorch Models using torch.compile on AMD GPUs with ROCm
Accelerate PyTorch Models using torch.compile on AMD GPUs with ROCm
Accelerating models on ROCm using PyTorch TunableOp
Accelerating models on ROCm using PyTorch TunableOp