Proceedings of the DATE Friday Workshop on System-level Design Methods for Deep Learning on Heterogeneous Architectures (SLOHA 2021)

TL;DR

This workshop volume compiles research on system-level design methods tailored for deep learning applications on heterogeneous hardware architectures, highlighting recent advances and challenges in this emerging field.

Contribution

It presents a collection of papers that introduce novel system-level design approaches specifically optimized for deep learning workloads on diverse hardware platforms.

Findings

Enhanced design methodologies for deep learning on heterogeneous architectures

Identification of key challenges in system-level optimization

Proposed frameworks improving efficiency and scalability

Abstract

This volume contains the papers accepted at the first DATE Friday Workshop on System-level Design Methods for Deep Learning on Heterogeneous Architectures (SLOHA 2021), held virtually on February 5, 2021. SLOHA 2021 was co-located with the Conference on Design, Automation and Test in Europe (DATE).