Efficient Execution of Irregular Dataflow Graphs

Efficient Execution of Irregular Dataflow Graphs

Hardware/Software Co-optimization for Probabilistic AI and Sparse Linear Algebra

von Nimish Shah, Wannes Meert, Marian Verhelst

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Beschreibung

This book focuses on the acceleration of emerging irregular sparse workloads, posed by novel artificial intelligent (AI) models and sparse linear algebra. Specifically, the book outlines several co-optimized hardware-software solutions for a highly promising class of emerging sparse AI models called Probabilistic Circuit (PC) and a similar sparse matrix workload for triangular linear systems (SpTRSV). The authors describe optimizations for the entire stack, targeting applications, compilation, hardware architecture and silicon implementation, resulting in orders of magnitude higher performance and energy-efficiency compared to the existing state-of-the-art solutions. Thus, this book provides important building blocks for the upcoming generation of edge AI platforms.

Produktdetails

ISBN 9783031331367
Verlag Springer Nature Switzerland
Erscheinungsdatum 13.07.2023
Sprache Englisch

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