Modular: AI’s compute fragmentation: what matrix multiplication teaches us
We are building a next-generation AI developer platform for the world. Read our latest post on how AI’s compute fragmentation: what matrix multiplication teaches us
Modular: AI’s compute fragmentation: what matrix multiplication teaches us Qualcomm to Acquire Modular. Read More → March 23, 2023 AI’s compute fragmentation: what matrix multiplication teaches us Eric Johnson Abdul Dakkak Chad Jarvis Engineering Compute fragmentation is holding AI back AI is powered by a virtuous circle of data, algorithms (“models”), and compute. Growth in one pushes needs in the others and can grossly affect the developer experience on aspects like usability and performance. Today, we have more data and more AI model research than ever before, but compute isn’t scaling at t
Explore this link on the map →related reading
- Modular: The world's fastest unified matrix multiplicationmodular.com
- How To Scale Your Modeljax-ml.github.io
- All About Rooflines | How To Scale Your Modeljax-ml.github.io
- Inside NVIDIA GPUs: Anatomy of high performance matmul kernels - Aleksa Gordićaleksagordic.com
- My picture of the present in AI — LessWronglesswrong.com
- The Short Case for Nvidia Stock | YouTube Transcript Optimizeryoutubetranscriptoptimizer.com
- Transformer Inference Arithmetic | kipply's blogkipp.ly
- A friendly introduction to machine learning compilers and optimizershuyenchip.com
- An Interview with MatX CEO Reiner Pope About LLM Chipschipstrat.com
- Reiner Pope of MatX on accelerating AI with transformer-optimized chipscheekypint.substack.com
- How to Think About TPUs | How To Scale Your Modeljax-ml.github.io
- The Best GPUs for Deep Learning in 2023 — An In-depth Analysistimdettmers.com