DLSpec: A Deep Learning Task Exchange Specification

02/26/2020
by   Abdul Dakkak, et al.
0

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.

READ FULL TEXT

page 1

page 2

page 3

research
08/24/2020

Bosch Deep Learning Hardware Benchmark

The widespread use of Deep Learning (DL) applications in science and ind...
research
11/19/2019

The Design and Implementation of a Scalable DL Benchmarking Platform

The current Deep Learning (DL) landscape is fast-paced and is rife with ...
research
09/27/2022

Deep Generative Multimedia Children's Literature

The popularity in Deep Learning (DL) based creative endeavours continues...
research
05/17/2021

How Deep is your Learning: the DL-HARD Annotated Deep Learning Dataset

Deep Learning Hard (DL-HARD) is a new annotated dataset designed to more...
research
11/19/2017

BPGrad: Towards Global Optimality in Deep Learning via Branch and Pruning

Understanding the global optimality in deep learning (DL) has been attra...
research
12/03/2020

Creativity of Deep Learning: Conceptualization and Assessment

While the potential of deep learning(DL) for automating simple tasks is ...
research
05/20/2022

Nothing makes sense in deep learning, except in the light of evolution

Deep Learning (DL) is a surprisingly successful branch of machine learni...

Please sign up or login with your details

Forgot password? Click here to reset