CGO 2020 : Symposium on Code Generation and Optimization

  in Conferences   Posted on June 21, 2019

Conference Information

Submission Deadline Friday 06 Sep 2019 Proceedings indexed by :
Conference Dates Feb 22, 2020 - Feb 26, 2020
Conference Address San Diego, United States
Conference & Submission Link https://cgo.org
Conference Organizers : ( Deadline extended ? Click here to edit )

Conference Ranking & Metrics (This is a TOP Conference)

Guide2Research Overall Ranking: 158
Category Rankings
Software Engineering & Programming 42
Computational Theory and Mathematics 15

Google Scholar H5-index:
26

Conference Call for Papers

=========================================================================

Call for Papers – International Symposium on Code Generation and Optimization (CGO) 2020

Including New Call for Tool and Practical Experience Papers

=========================================================================

Co-located with PPoPP and HPCA

Feb 22nd to 26th, 2020, San Diego, USA

http://cgo.org

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 optimization.

======== Important Dates (AOE) ============

August 30, 2019: Abstract Submission

Sept 6, 2019: Paper Submission

Oct 9th-10th, 2019: Author Rebuttal Period

Oct 22nd, 2019: Paper Notification

Original contributions are solicited on, but not limited to, the following topics:

• 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 debugging

• 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 synchronization

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 Library.

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 repository of benchmarks for testing should be provided.

• 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.

============= Organization Committee ==================

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

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

============= 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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