@satvikgari: Wake up the goat posted
Summary
A progress update on reinventing Groq's LPU, with a redesigned vector execution module to better support overlap operations and self-attention.
View Cached Full Text
Cached at: 06/01/26, 07:49 PM
Wake up the goat posted
michael.trbo (@michael_trbo): another progress update on reinventing Groq’s LPU with @sakshambatraa:
we redesigned out vector execution module (VXM) to better support overlap on operations, and introduce compatibility to run self attention!
Similar Articles
@derangineer: the goats in the game
Charles Frye announces a blog post detailing contributions to FA4 internals, focusing on inference performance improvements that have been upstreamed.
@levidiamode: 163/365 of GPU Programming Looking at a few different agentic GPU kernel optimization systems today. The two I'm most i…
A tweet discussing two agentic GPU kernel optimization systems: Auto GPU Kernel by @dogacel0 and Kernel Design Agents from @songhan_mit's lab, both winners at the MLSys Sparse Attention FlashInfer competition. The thread highlights different approaches using subagents and Claude skills for GPU programming.
Developing open source LLM from ground up from pretrain - rlhf(PPO/GRPO)
A developer shares progress on training a 7B parameter open source LLM from scratch using a DeepSeek architecture optimized for low VRAM, with the goal of democratizing AI development and eventually surpassing large proprietary models.
@akshay_pachaar: https://x.com/akshay_pachaar/status/2064700531600458093
This article explains how to use GRPO to fine-tune an LLM (Qwen3-8B) for reliable JSON structured output, improving schema accuracy from 62% to 82%, surpassing GPT-4.1's 58%.
@charles_irl: Rewriting parallelism is a big move and it'd be nice to make it even faster than we can do with CuTe DSL. FA4 is a very…
Discussion about rewriting parallelism to improve kernel performance using CuTe DSL and tile programming models for the FA4 (FlashAttention 4) kernel.