Lingjia Tang

TL;DR: Continuous shape shifiting is introduced, a compilation approach that removes the risks of cache tiling optimizations by dynamically rewriting (and reshaping) deployed, running application code by presenting ShapeShifter, a framework for continuous monitoring of co-running applications and their runtime environments to reshape loop iteration spaces and pinpoint near-optimal loop tile configurations.

TL;DR: It is demonstrated that OFA is able to automatically and accurately integrate an ensemble of commercially available CAs spanning disparate domains, and using the MARS encoder the authors achieve the highest accuracy on the BBAI task, outperforming strong baselines.

TL;DR: In this article, the authors present a system for intelligent formation and acquisition of machine learning training data for implementing an artificially intelligent dialogue system, which includes constructing a corpora of ML test corpus that comprise a plurality of historical queries and commands sampled from production logs of a deployed dialogue system.

TL;DR: VMT is proposed, a thermal aware job placement technique that adds an active, tunable component to enable greater control over datacenter thermal output and reduces peak cooling load by up to 12.8% to provide over two million dollars in cost savings when a smaller cooling system is installed.

TL;DR: In this article, the authors proposed a method to allocate tasks among computing machines in large scale computing systems, where the predicted performance degradation is determined by comparing a performance interference score of the second task with a performance sensitivity curve of the first task.