Archive of posts tagged: Machine Learning
Architecture 2.0: Why Computer Architects Need a Data-Centric AI Gymnasium
Machine learning driven computer architecture tools and methods have the potential to drastically shape the future of computer architecture. The question is: how can we lay the foundation to effectively usher in this era? In this post, we delve into the transformative...
Is It Time To Give Memory Allocator Its Own Room In The House?
Implications of Machine Learning (ML), be the training or inference serving, have steered systems and architecture research accordingly. A significant amount of work is happening in the Systems for ML space ranging from building efficient systems for data...
Picking Your Research Direction: Trade-offs You Should Consider
Modern research in computer architecture has been developed far beyond the conventional textbook topics of processor microarchitectures and memory hierarchies, now expanding to a much more diverse range of novel areas. Computer architects can explore many promising...
Coping with Copilot
CS educators: AI-based developer tools are gunning for your assignments. Resistance is futile GitHub’s AI-based Copilot tool went public this summer. It’s an amazing tool for software developers. But students armed with it will be bringing Uzis to a knife fight. Using...Subscribe
