Free shipping on orders over 19,990 Ft via Packeta, Fox Post Box, and DPD Collection Point

Check order status

Become part of a community of book lovers from all over the world and get access to a whole bunch of benefits. Create an account for free

Free delivery for purchases over 19 990 Ft

DPD courier 1 190 Ft Post 1 795 Ft Post 1 690 Ft Post 1 690 Ft FoxPost 1 190 Ft Packeta point 1 190 Ft DPD point 990 Ft GLS courier 1 690 Ft GLS point 1 190 Ft

Contact

How to shop

Help

My account

▸ Empty :-(

Free shipping on orders over 19,990 Ft via Packeta, Fox Post Box, and DPD Collection Point

Efficient Execution of Irregular Dataflow Graphs

Name: Efficient Execution of Irregular Dataflow Graphs
Brand: Springer, Berlin
SKU: 43225187
Price: 30759 HUF
Availability: InStock
Author: Nimish Shah
ISBN: 9783031331350

Hardware/Software Co-optimization for Probabilistic AI and Sparse Triangular Systems

Nimish Shah

Marian Verhelst

Wannes Meert

Language

English

Book Hardback

Libristo code: 43225187

Publishers Springer, Berlin, September 2023

This book focuses on the acceleration of emerging irregular sparse workloads, posed by novel artific... Full description

Libristo code: 43225187

212 b

30 759 Ft

In stock at our supplier Shipping in 10-13 days

Up to 30 days for returns

Customers also purchased

Français-Serbe (Cyrillique) Véhicules Imagier bilingue pour les enfants Richard Carlson Jr

Paperback

4 403 Ft

Landesverfassungsgerichte Werner Reutter

Hardback

28 763 Ft

Deutsches Seemaennisches Soerterbuch Alfred Stenzel

Paperback

8 805 Ft

Obsesion de la Narcisista Jairo E Lopez

Paperback

3 663 Ft

Histoire De La Réformation De La Suisse, Volume 5 Louis Vulliemin

Paperback

11 586 Ft

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.