ISMM 2019

The ACM SIGPLAN International Symposium on Memory Management (ISMM 2019) is soliciting full-length submissions covering new work on all memory management related topics, as well as papers presenting confirmations or refutations of important prior results. Surveys and comparative analyses that shed new light on previously published techniques are also welcome.

Areas of interest include but are not limited to:

Memory system design and analysis
Hardware support for memory management
Memory management for large-scale data-intensive systems
Novel memory architectures
Memory management at datacenter and cloud scales
Garbage Collection algorithms and implementations
Formal analysis and verification of memory management algorithms
Compiler analyses to aid memory management
Tools to analyze memory usage of programs
Memory allocation and de-allocation
Empirical analysis of memory intensive programs
Formal analysis and verification of memory intensive programs

All papers must be submitted on-line in Portable Document Format (PDF). The submission site will be at http://ismm2019.hotcrp.com.

The Program Committee (PC) and External Review Committee (ERC) will read submissions and judge them on scientific merit, innovation, readability, and relevance. Papers previously published or already being reviewed by another conference are not eligible. If a closely related paper has been submitted elsewhere, the authors must notify the Program Chair as per the SIGPLAN republication policy. Papers should be self-contained. Reviewers are not required to read appendices, so a paper should be intelligible without them. Supplemental or auxiliary materials are not accepted.

Submission Site

All papers should be submitted via https://ismm2019.hotcrp.com.

Paper Template

Submissions must be in English and papers should be formatted according to the two-column ACM proceedings format. Each paper should have no more than 10 12 pages, excluding bibliography and any appendices, in ~~9pt~~ 10pt font. There is no limit on the page count for references. Each reference must list all authors of the paper (do not use et al). The citations should be in numeric style, e.g., [52]. Submissions should be in PDF format and printable on US Letter and A4 sized paper. Make sure that figures and tables are legible, even after the paper is printed in gray-scale. See Important Dates for the submission deadline.

As explained in more detail at http://www.sigplan.org/Resources/Author, LaTeX users should use the (new) sigplan subformat of the (new) acmart format by downloading acmart-sigplanproc.zip. Word users should use the acmart template for Word. Please note the following:

acmart-sigplanproc-template.tex has the following defaults for ISMM 2019 submissions … the initial lines say:

\documentclass[sigplan,10pt,review,anonymous]{acmart}

\settopmatter{printfolios=true,printccs=false,printacmref=false}

The default citation style is numeric, and the defaults are correct for ISMM.
Do not mess with the class file or settings to try to sneak in additional space. (Conversely, you may toggle the printccs and printacmref flags if you wish, but this will consume space.)
Do not use the PACMPL files or format; ISMM is not using them. However, the template files were designed to make migrating a paper from one format to the other as simple as possible.
Papers that violate the above guidelines will be rejected by the Program Chair.

All accepted papers will appear in the published proceedings.

Double-Blind Reviewing

The ISMM paper reviewing process is double blind: authors are not known to the reviewers and reviewers are not known to authors. This is to authors’ benefit, since research indicates that author anonymity reduces bias in reviewing. Authors are required to make reasonable efforts not to disclose their identities to reviewers. For example, authors should not attach names nor mention institution, research group, project name, etc. Authors should refer to projects and prior work in the third person, e.g. “the XYZ project” or work by “Author et al.”, as with discussion of all related work. Where necessary for flow, authors may add a footnote that a name is withheld for review. Paper drafts should not be made public to reduce the possibility of inadvertently revealing author identity to reviewers. Reviewers are honor-bound not to try to discover authors’ identities, which will be known only by the Program chair until the appropriate point in the Program Committee’s deliberations. Authors are required to declare known conflicts with members of the PC and ERC at submission time, as defined by SIGPLAN guidelines: http://www.sigplan.org/Resources/Policies/Review/

External Review Committee

ISMM 2019 follows the practice introduced at earlier instances of ISMM of using a separate External Review Committee as part of the reviewing process. The ERC complements the Program Committee by providing a broader and deeper pool from which to draw expert reviews. The same reviewing standards apply to the ERC as for the PC. However, ERC members review fewer papers and do not participate in the PC meeting. ERC members review and decide acceptance for submissions by PC members. This approach should be more practical with double-blind reviewing than ad hoc expert review assignments as used by a number of conferences. The formal selection process, transparency of its constituency, and the fact that each reviewer will review multiple papers should increase the quality and accountability of reviews as compared to traditional ad hoc expert review assignments.

Rebuttal

The rebuttal process will occur in early April (see Important Dates), and will give the authors an opportunity to respond to factual errors in reviews before the Program Committee meets to make its decisions. The committee may, but need not, respond to rebuttals or revise reviews at or after the committee meeting.

Acknowledgments

This call-for-papers is an adaptation and evolution of content from previous instances of ISMM and PLDI. We are grateful to prior organizers for their work, which is reused here.

ISMM 2019

Accepted Papers

Concurrent Marking of Shape-Changing Objects

Massively Parallel GPU Memory Compaction,

Snmalloc: A message passing allocator

Design and Analysis of Field-Logging Write Barriers

A Lock-Free Coalescing-Capable Mechanism for Memory Management

Learning When to Garbage Collect with Random Forests

Automatic GPU Memory Management for Large Neural Models in TensorFlow

Scaling Up Parallel GC Work-Stealing in Many-Core Environments

Gradual Write-barrier Insertion into a Ruby interpreter

Online Timescale Theory for Concurrent Memory Allocation

Exploration of Memory Hybridization for RDD Caching in Spark

ISMM 2019: Call for Papers