DLSpec: A Deep Learning Task Exchange Specification

Abstract

Deep Learning (DL) innovations are being introduced at a rapid pace. However, the current lack of standard specification of DL tasks makes sharing, running, reproducing, and comparing these innovations difficult. To address this problem, we propose DLSpec, a model-, dataset-, software-, and hardware-agnostic DL specification that captures the different aspects of DL tasks. DLSpec has been tested by specifying and running hundreds of DL tasks.

Cheng Li

Member of Technical Staff

I specialize in building efficient AI training and inference systems using GPUs, with a focus on optimizing performance for Large Language Models (LLMs) and Large Vision Models (LVMs).