Archive of posts tagged: Machine Learning
The QuArch Experiment: Crowdsourcing a Machine Learning Dataset for Computer Architecture
Introduction The rise of large language models (LLMs) and generative artificial intelligence (GenAI) presents new opportunities to build innovative tools and is already enabling revolutionary AI-based tools in various domains. However, a significant gap remains in the...
Efficient GEMM Kernel Designs with Pipelining
General Matrix Multiplication (GEMM) is a fundamental operation in machine learning and scientific computing. It is the classic example of an algorithm that benefits greatly from GPU acceleration due to its high degree of data parallelism. More recently, efficient...
TinyML: Why the Future of Machine Learning is Tiny and Bright
At the dawn of the 21st century, Mark Weiser envisioned a world where computers would weave themselves into the fabric of everyday life, becoming indistinguishable from it. This prophecy of ubiquitous computing has not only materialized but has evolved beyond...
AI Software Should be More Like Plain Old Software
A Tale of Two Softwares: In a world where AI is revolutionizing the way we interact with technology, a new type of software emerges: AI Software (AISW). But with great power comes great responsibility, and the systems research community must rise to the challenge of ensuring AISW is as robust, secure, and safe as its predecessor, Plain Old Software (POSW).
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