computingComputer Science and Technologies

The ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC) is the premier annual conference for presenting the latest research on the design, implementation, evaluation, and the use of parallel and distributed systems for high-end computing.

Every paper accepted for HPDC 2022 will be published in the proceedings. We will also guarantee valuable interaction on the papers to be presented.

General Chairs:
Jon Weissman University of Minnesota, MN, USA
Abhishek Chandra University of Minnesota, MN, USA

Program Chairs:
Ada Gavrilovska Georgia Institute of Technology, GA, USA
Devesh Tiwari Northeastern University, MA, USA

Publications Chair:
Antonino Tumeo PNNL, WA, USA

Workshops Chair:
Ivy Peng Lawrence Livermore National Laboratory, CA, USA
Poster and Travel Grant Chair:
Dong Li University of California, Merced, USA

Publicity Co-Chairs:
Kento Sato RIKEN Center for Computational Science (RIKEN R-CCS), Japan
Ali Anwar IBM Research, Almaden Research Center, CA, USA

Social Media Chair:
Thaleia Dimitra Doudali IMDEA Software Institute, Madrid, Spain

Web Master:
Nikhil Sreekumar University of Minnesota, MN, USA

Scope and Topics
Submissions are welcomed on high-performance parallel and distributed computing (HPDC) topics including but not limited to: clouds, clusters, grids, big data, massively multicore, and extreme-scale computing systems. Experience reports of operational deployments that provide significantly novel insights for future research on HPDC applications and systems are also welcome.

In the context of high-performance parallel and distributed computing, the topics of interest include, but are not limited to:

Datacenter, HPC, cloud, serverless, and edge/IoT computing platforms
Heterogeneous computing accelerators and non-volatile memory systems
File and storage systems, I/O, and data management
Operating systems and networks
System software and middleware for parallel and distributed systems
Programming languages and runtime systems
Big data stacks and big data ecosystems
Scientific applications, algorithms, and workflows
Resource management and scheduling
Performance modeling, benchmarking, and engineering
Fault tolerance, reliability, and availability
Operational guarantees, risk assessment, and management
Novel post-Moore computing technologies including neuromorphic, brain-inspired computing, and quantum computing.