Tiled algorithms, in general, divide the problem into smaller, manageable tiles that fit into faster, but limited-size memory, be it cache, shared memory, or registers, to improve memory access patterns. Many problems which often involve matrices, can be broken down into tiles. This improves cache utilization which improves cache hit/miss ratio, by reusing data within smaller subproblems. In this post we implement tiled matrix multiplication.

At CES 2025 event, NVIDIA announced, among other interesting things, including a single chip made out of72 Blackwell GPUs, with 1.5 ExaFLOPS performance, it’s first world foundation model, Cosmos. DeepMind is working on a similar model, and this is also one of xAI’s core missions. I suspect that these models are among the next frontier in scientific and AI research, following AlphaFold’s breakthroughs in protein folding prediction.

Recently I gave a talk/mini workshop on spack package manager at SKAO, for which I dug into the core of spack. Spack boasts itself as the package manager for HPC, and it really is. The idea is straightforward, streamline what we normally do when compiling and installing software manually on HPC systems using Python. It’s a simple idea but not at all easy to implement.