Overview

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.

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 will also receive special consideration.

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

    Operating systems, networks, and architectures
    High performance runtime environments
    Massively multicore systems, including heterogeneous systems
    Datacenter technology, resource virtualization
    Programming languages, APIs, and system interoperation approaches
    File and storage systems, I/O, and data management
    Big data stacks and big data ecosystems
    Resource management and scheduling, including energy-aware techniques
    Performance modeling, analysis, and engineering
    Fault tolerance, reliability, and availability
    Operational guarantees, risk assessment, and management
    Emerging application areas that include cloud/edge computing and IoT

Submission Guidelines

Authors are invited to submit technical papers of at most 12 pages in PDF format, including figures and references. Papers should be formatted in the ACM Proceedings Style and submitted via the conference web site. Submitted papers must be original work that has not appeared in and is not under consideration for another conference or a journal.

Submissions to HPDC 2020 are double blind.

Anonymizing Submissions

HPDC will use double-blind reviewing this year. Please make a good faith attempt to anonymize your submission. Avoid identifying yourself or your institution explicitly or by implication (e.g., through the references or acknowledgments). The first page should use the paper ID assigned during registration in place of the author names.

Use care in referring to your own related work. Do not omit references to your prior work, as this would make it difficult for reviewers to place your submission in its proper context. Instead, reference your past work in the third person, just as you would any other piece of related work. In some cases, it is not credible to refer to your related work in the third person. For example, your submission may extend a previous workshop paper, or it may relate to a submission currently under review at HPDC or another venue. In these cases, you must still explain the differences between your HPDC submission and the other work, but you should cite the other work anonymously and e-mail the deanonymized work to the PC chairs.

If your submission reports on experiences with a system at your institution, you should refer to the system anonymously but describe the properties of the system that are needed to appreciate the work (e.g., size of the user base, volume of requests, etc.). We recognize that, in some cases, these properties may allow a reviewer to identify your institution.