Posts by Clint Greene
Supercharging JAX with Triton Kernels on AMD GPUs
- 09 October 2024
Ready to supercharge your deep learning applications on AMD GPUs? In this blog, we’ll show you how to develop a custom fused dropout activation kernel for matrices in Triton, seamlessly call it from JAX, and benchmark its performance with ROCm. This powerful combination will take your model’s performance to the next level.
Fine-tuning Llama 3 with Axolotl using ROCm on AMD GPUs
- 23 September 2024
Large Language Models (LLMs) have revolutionized the field of natural language processing, enabling machines to understand and generate human-like language. However, these models are often trained on vast amounts of general-purpose data, which can make them less effective for specific tasks or domains. Fine-tuning involves training a pre-trained LLM on a specialized dataset to enhance its performance on specific tasks. As Andrej Karpathy analogized, this process is akin to allowing someone to practice a particular skill. Just as a person might need to practice a skill in a specific context to become proficient, an LLM needs to be fine-tuned on a specific dataset to become proficient in a particular task. For instance, an LLM can be fine-tuned for tasks such as financial forecasting, technical support, legal advising, medical diagnosis, or even instruction following. By fine-tuning an LLM, organizations can achieve better results and improve information security by limiting the exposure of sensitive data.
Accelerating Large Language Models with Flash Attention on AMD GPUs
- 15 May 2024
15, May 2024 by Clint Greene.
Accelerating XGBoost with Dask using multiple AMD GPUs
- 26 January 2024
26 Jan, 2024 by Clint Greene.