DIDL 2020 : Fourth Workshop on Distributed Infrastructures for Deep Learning

Deep learning is a rapidly growing field of machine learning, and has proven successful in many domains, including computer vision, language translation, and speech recognition. The training of deep neural networks is resource intensive, requiring compute accelerators such as GPUs, as well as large amounts of storage and memory, and network bandwidth. Additionally, getting the training data ready requires a lot of tooling for data cleansing, data merging, ambiguity resolution, etc. Sophisticated middleware abstractions are needed to schedule resources, manage the distributed training job as well as visualize how well the training is progressing. Likewise, serving the large neural network models with low latency constraints can require middleware to manage model caching, selection, and refinement.

DIDL 2020 : Fourth Workshop on Distributed Infrastructures for Deep Learning will take place in UC Davis, CA. It’s a 5 days event starting on Dec 09, 2020 (Wednesday) and will be winded up on Dec 13, 2020 (Sunday).

DIDL 2020 falls under the following areas: DEEP LEARNING, NEURAL, ALGORITHMS, etc. Submissions for this Workshop can be made by Aug 31, 2020. Authors can expect the result of submission by Sep 28, 2020. Upon acceptance, authors should submit the final version of the manuscript on or before Oct 16, 2020 to the official website of the Workshop.

Please check the official event website for possible changes before you make any travelling arrangements. Generally, events are strict with their deadlines. It is advisable to check the official website for all the deadlines.

Other Details of the DIDL 2020

• Short Name: DIDL 2020
• Full Name: Fourth Workshop on Distributed Infrastructures for Deep Learning
• Timing: 09:00 AM-06:00 PM (expected)
• Fees: Check the official website of DIDL 2020
• Event Type: Workshop
• Website Link: https://didl-conf.github.io/didl4/cfp.html
• Location/Address: UC Davis, CA