Interactive services, such as Web search, recommendations, games, and finance, must
respond quickly to satisfy customers. Achieving this goal requires optimizing tail (eg, 99th+ …

Future multicore processors will be heterogeneous, be increasingly less reliable, and
operate in dynamically changing operating conditions. Such environments will result in a …

Stream processing applications are common computing workloads that demand parallelism
to increase their performance. As in the past, parallel programming remains a difficult task …

Interactive web services increasingly drive critical business workloads such as search,
advertising, games, shopping, and finance. Whereas optimizing parallel programs and …

With the proliferation of AI-based applications and services, there are strong demands for
efficient processing of deep neural networks (DNNs). DNNs are known to be both compute …

Given the wide scale adoption of multi-cores in main stream computing, parallel programs
rarely execute in isolation and have to share the platform with other applications that …

The success of machine learning has prospered Machine-Learning-as-a-Service (MLaaS)-
deploying trained machine learning (ML) models in cloud to provide low latency inference …

A web search query made to Microsoft Bing is currently parallelized by distributing the query
processing across many servers. Within each of these servers, the query is, however …

The ubiquity of parallel machines will necessitate time-and energy-efficient parallel
execution of a program in a wide range of hardware and software environments. Prevalent …

Workload, platform, and available resources constitute a parallel program's execution
environment. Most parallelization efforts statically target an anticipated range of …