Optimizing

I work on Dolt, the first SQL database with git-like version control, written entirely in Go. And as a rule, databases need to be fast. So we have lots of tests in our CI workflow to monitor performance regressions before … Read more

Abstract:A major challenge in training large-scale machine learning models is configuring the training process to maximize model performance, i.e., finding the best training setup from a vast design space. In this work, we unlock a gradient-based approach to this problem. … Read more

Introduction Hi everyone ! In this post, I will share with you all the steps to write an optimized FP32 matrix multiplication on AMD RDNA3 GPU outperforming rocBLAS by 60%. I will cover some basics and explain all the optimizations … Read more

January 15, 2025 · 4 mins · 762 words I’ve been using LLM-assisted coding for the last couple of months, and it has been a game-changer. After a couple of iterations, my setup consists in ContinueDev + OpenRouter. I’m using … Read more

In the previous post, we established that as long as ruby/json wasn’t competitive on micro-benchmarks, public perception wouldn’t change. Since what made ruby/json appear so bad on micro-benchmarks was its setup cost, we had to find ways to reduce it … Read more

I was recently made maintainer of the json gem, and aside from fixing some old bugs, I focused quite a bit on its performance, so that it is now the fastest JSON parser and generator for Ruby on most benchmarks. … Read more

Building Surfgrad, a high-performant, WebGPU-powered autograd library I work at Nomic, where many of my colleagues work on building large TSNE-like visualizations work in the browser1. Showing tens of millions of data points in the browser without rendering your computer … Read more