Posts by Aditya Kumar Singh

GEAK V3: Agent-Driven, Repository-Level GPU Kernel Optimization across HIP, Triton, and FlyDSL on AMD GPUs

In the ever-evolving world of GPU computing, optimizing kernels for performance and efficiency is a critical challenge. Hand-tuning kernels demands deep technical expertise and manual iteration. In this blog, you will read about how GEAK v3, the latest iteration of the agent-driven framework, tackles this problem using enhanced features such as task planning, test-harness discovery, patch-based handling of multi-file kernels, dynamic memory system and expert knowledge database. Our results show improvements across three kernel languages (HIP, Triton, and FlyDSL) and both CDNA and RDNA GPUs.

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Instella-VL-1B: First AMD Vision Language Model

As part of AMD’s newly released Instella family we are thrilled to introduce Instella-VL-1B, the first AMD vision language model for image understanding trained on AMD Instinct™ MI300X GPUs. Our journey with Instella-VL builds upon our previous 1-billion-parameter language models, AMD OLMo SFT. We further extend the language model’s visual understanding abilities by connecting it with a vision encoder (which is initialized from CLIP ViT-L/14-336). During training, we jointly finetune vision encoder and language model with vision-language data in three stages: Alignment, Pretraining and Supervised-Finetuning (SFT).

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