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Message posted on 12/06/2019

CfP: Code Generation and Optimization 2020 (Abstracts Due August 30)

IEEE/ACM International Symposium on Code Generation and Optimization (CGO)
co-located with PPoPP and HPCA
San Diego, CA, USA
February 22 - 26, 2020

The International Symposium on Code Generation and Optimization (CGO) provides
a premier venue to bring together researchers and practitioners working at the
interface of hardware and software on a wide range of optimization and code
generation techniques and related issues. The conference spans the spectrum
from purely static to fully dynamic approaches, and from pure software-based
methods to specific architectural features and support for code generation and

Abstract Submission: August 30, 2019
Paper Submission: September 6, 2019
Author Rebuttal Period: October 9 - 10, 2018
Paper Notification: October 22, 2019

Original contributions are solicited on, but not limited to, the following
– Code Generation, Translation, Transformation, and Optimization for
performance, energy, virtualization, portability, security, or reliability
concerns, and architectural support
– Efficient execution of dynamically typed and higher-level languages
Optimization and code generation for emerging programming models, platforms,
domain-specific languages Dynamic/static, profile-guided, feedback-directed,
and machine learning based optimization
– Static, Dynamic, and Hybrid Analysis for performance, energy, memory
locality, throughput or latency, security, reliability, or functional
– Program characterization methods
– Efficient profiling and instrumentation techniques; architectural support
– Novel and efficient tools
– Compiler design, practice and experience
– Compiler abstraction and intermediate representations
– Vertical integration of language features, representations, optimizations,
and runtime support for parallelism
– Solutions that involve cross-layer (HW/OS/VM/SW) design and integration
– Deployed dynamic/static compiler and runtime systems for general purpose,
embedded system and Cloud/HPC platforms
– Parallelism, heterogeneity, and reconfigurable architectures
– Optimizations for heterogeneous or specialized targets, GPUs, SoCs, CGRA
– Compiler support for vectorization, thread extraction, task scheduling,
speculation, transaction, memory management, data distribution and

The Artifact Evaluation process is run by a separate committee whose task is
to assess how the artifacts support the work described in the papers. Authors
of accepted papers have the option of submitting their artifacts for
evaluation within two weeks of paper acceptance. To ease the organization of
the AE committee, we kindly ask authors to indicate at the time they submit
the paper, whether they are interested in submitting an artifact. Papers that
go through the Artifact Evaluation process successfully will receive a seal of
approval printed on the papers themselves. Additional information is available
on the CGO AE web page. Authors of accepted papers are encouraged, but not
required, to make these materials publicly available upon publication of the
proceedings, by including them as “source materials” in the ACM Digital


This year, CGO has a special category of papers called “tools and practical
experience”. Such a paper is subject to the same page length guidelines,
except that it must give a clear account of its functionality and a summary
about the practice experience with realistic case studies, and describe all
the supporting artifacts available. The selection criteria are:

– Originality: Papers should present CGO-related technologies applied to
real-world problems with scope or characteristics that set them apart from
previous solutions.
– Usability: The presented Tools or compilers should have broad usage or
applicability. They are expected to assist in CGO-related research, or could
be extended to investigate or demonstrate new technologies. If significant
components are not yet implemented, the paper will not be considered.
– Documentation: The tool or compiler should be presented on a web-site
giving documentation and further information about the tool.
– Benchmark Repository: A suite of benchmarks for testing should be
– Availability: Preferences will be given to tools or compilers that are
freely available (at either the source or binary level). Exceptions may be
made for industry and commercial tools that cannot be made publicly available
for business reasons.
– Foundations: Papers should incorporate the principles underpinning Code
Generation and Optimization (CGO). However, a thorough discussion of
theoretical foundations is not required; a summary of such should suffice.


Authors should carefully consider the difference in focus with the co-located
conferences when deciding where to submit a paper. CGO will make the
proceedings freely available via the ACM DL platform during the period from
two weeks before to two weeks after the conference. This option will
facilitate easy access to the proceedings by conference attendees, and it will
also enable the community at large to experience the excitement of learning
about the latest developments being presented in the period surrounding the
event itself.

General Chairs
Jason Mars, University of Michigan
Lingjia Tang, University of Michigan

Program Chairs
Jingling Xue, UNSW Sydney
Peng Wu, Futurewei Technologies

Workshop and Tutorials Chairs
Johann Hauswald, Clinc
Yunqi Zhang, Clinc

Artifact Evaluation Chairs
Bastian Hagedorn, University of Münster
Michael Laurenzano, University of Michigan/Clinc
Michel Steuwer, University of Glasgow

Student Research Competition Chair
Changhee Jung, Purdue University

Student Travel Grants Chair
Animesh Jain, Amazon

Treasurer/Finance Chair
Christophe Dubach, University of Edinburgh

Publicity Chair
Fabian Gruber, Inria

Registration Chair
Dongyoon Lee, Virgina Tech

Web Chair
Dongjie He, UNSW Sydney

Steering Committee
Aaron Smith, Microsoft Research
Carol Eidt, Microsoft
Fabrice Rastello, Inria
Jack W. Davidson, University of Virginia
Jason Mars, University of Michigan
Teresa Johnson, Google

Program Committee
Aaron Smith, Microsoft/Edinburgh University
Andrew Adams, Facebook
Antonia Zhai, University of Minnesota
Ben Hardekopf, UCSB
Björn Franke, University of Edinburgh
Bruce R. Childers, University of Pittsburgh
Changhee Jung, Purdue University
Christophe Dubach, University of Edinburgh
Damian Dechev, University of Central Florida
Derek Bruening, Google
Erik Altman, IBM
Fabrice Rastello, Inria
Fredrik Kjolstad, MIT
Gennady Pekhimenko, University of Toronto
Guilherme Ottoni, Facebook
Guoyang Chen, Alibaba Group US Inc
Huimin Cui, Chinese Academy of Sciences
Jaejin Lee, Seoul National University
J Nelson Amaral, University of Alberta
Lisa Wu, UC Berkeley
Louis-Noël Pouchet, Colorado State University
Mahmut T. Kandemir, Pennsylvania State University
Maria Garzaran, Intel/UIUC
Michel Steuwer, University of Glasgow
Pen-Chung Yew, University of Minnesota
Raj Barik, Uber
Rajiv Gupta, UC Riverside
Sanjay Rajopadhye, Colorado State University
Simone Campanoni, Northwestern University
Snehasish Kumar, Google
Sreepathi Pai, University of Rochester
Svilen Kanev, Google
Teresa Johnson, Google
Timothy M. Jones, University of Cambridge
Tobias Grosser, ETH Zurich
Vijay Janapa Reddi, Harvard University
Walter Binder, University of Lugano
Xipeng Shen, North Carolina State University
Xu Liu, College of William and Mary
Zheng Wang, Lancaster University
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