Explore the intersection of software and hardware for sparse machine learning in this 18-minute conference talk presented at CTSTA'23. Gain insights into the latest advancements and techniques in developing efficient systems for sparse ML applications. Discover how specialized software and hardware solutions can optimize performance and resource utilization in machine learning models that deal with sparse data structures. Learn about cutting-edge approaches that address the unique challenges of sparse ML, including data representation, computation, and memory management.
Overview
Syllabus
[CTSTA'23] Software and Hardware for Sparse ML
Taught by
ACM SIGPLAN
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