This is a contributed blog to the series run by Berkeley's Sky Computing Lab.

In this blog post, we examine the problem of balancing memory and other knowledge sources for GPU kernel generation agents. Memory helps GPU kernel agents only when it saves more search than it costs in context. Search discovers useful coding patterns, and memory prevents rediscovering them.

Read the full blog on their website, here: https://ucbskyadrs.github.io/blog/makora/