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| ACM SIGPLAN Symposium on Compiler Construction | |
|---|---|
| Name | ACM SIGPLAN Symposium on Compiler Construction |
| Abbreviation | CC |
| Discipline | Computer science; Programming languages; Software engineering |
| Venue | Rotating international locations |
| First | 1996 |
| Organizer | Association for Computing Machinery; SIGPLAN |
| Frequency | Annual |
ACM SIGPLAN Symposium on Compiler Construction is an annual technical symposium focused on compiler design, implementation, optimization, and related tooling. It brings together researchers and practitioners from institutions such as Massachusetts Institute of Technology, Stanford University, University of California, Berkeley, Carnegie Mellon University, and University of Cambridge alongside industry teams from Google, Microsoft, Amazon (company), Intel, and NVIDIA. The symposium serves as a venue for presenting novel algorithms, systems, and empirical studies linking work at Princeton University, ETH Zurich, Imperial College London, University of Toronto, and University of Illinois Urbana–Champaign.
The symposium originated amid growing interest in optimizing compilers during the 1990s, following advances associated with groups at Bell Labs, Xerox PARC, DEC (Digital Equipment Corporation), IBM Research, and Hewlett-Packard. Early meetings featured contributors from GNU Project, LLVM Project, GCC (GNU Compiler Collection), Java (programming language), and researchers influenced by landmarks such as Donald Knuth's work and projects at University of Washington. Over time the event attracted submissions from labs connected to Oracle Corporation, Sun Microsystems, Lucent Technologies, Siemens AG, and national research bodies including National Science Foundation-funded teams and European consortia tied to European Research Council projects. The symposium evolved to reflect shifts toward just-in-time compilation debated alongside research at Brown University, University of Edinburgh, and University of Pennsylvania.
Topics encompass static and dynamic compilation research from groups at MIT Lincoln Laboratory, Los Alamos National Laboratory, Sandia National Laboratories, and startups spun out of University of California, Santa Barbara. Typical themes include program analysis methods originating from Ayres (static analysis), optimization frameworks related to Polyhedral model, code generation techniques influenced by work at ARM Holdings, and runtime systems with ancestry to HotSpot VM. Papers often cite lineage from projects at PARSEC (benchmark) authors, investigations connected to SPEC CPU suites, and concurrency issues paralleling research at University of Michigan and Columbia University.
The symposium is organized by Association for Computing Machinery's Special Interest Group on Programming Languages, with program committees drawing members from SIGPLAN (ACM), editorial boards of journals such as ACM Transactions on Programming Languages and Systems, and steering committees including representatives from IEEE Computer Society and industrial partners like Apple Inc. and Facebook (company). Funding and sponsorship historically include grants from National Institutes of Health for bioinformatics-related compiler toolchains, corporate sponsorships from Red Hat, ARM, Qualcomm, and collaboration with workshops associated with PLDI (conference), POPL (conference), and OOPSLA.
Papers presented at the symposium have advanced areas tied to research by Frances E. Allen, John Cocke, Monica S. Lam, Chris Lattner, and Susan Horwitz. Contributions include influential work on SSA form extending concepts from Ron Cytron's group, register allocation schemes related to Chaitin (graph coloring), and just-in-time techniques echoing innovations from Sun Microsystems and the HotSpot team. Implementations and case studies reported at the symposium have influenced projects such as GraalVM, LLVM Project, GCC (GNU Compiler Collection), and domain-specific compilers used in initiatives like TensorFlow and PyTorch. Empirical methodologies published at CC drew upon benchmark suites like SPEC and datasets curated in collaboration with National Institute of Standards and Technology.
The symposium typically features peer-reviewed paper sessions, invited talks from luminaries associated with Turing Award winners and recipients of ACM SIGPLAN Programming Languages Achievement Award, poster sessions, tutorials, and tool demonstrations developed at institutions like Microsoft Research and Google Research. Awards presented include best paper recognitions often paralleling accolades at PLDI (conference), artifact awards inspired by policies at ICLR and NeurIPS, and student paper prizes tied to fellowships from ACM and corporate donors such as NVIDIA. Workshops co-located with the symposium mirror formats used by CCS (conference) and Usenix events.
Accepted papers are published in ACM proceedings indexed through ACM Digital Library and cross-listed with proceedings of related meetings such as International Conference on Architectural Support for Programming Languages and Operating Systems and International Symposium on Code Generation and Optimization. Extended versions frequently appear in journals like ACM Transactions on Architecture and Code Optimization and Science of Computer Programming, with archival records maintained alongside bibliographic entries in DBLP and citation tracking via Google Scholar.
The symposium fosters a community connecting academia and industry, bridging researchers from University of California, Los Angeles, Ecole Polytechnique Fédérale de Lausanne, Technical University of Munich, and industrial labs at IBM Watson Research Center. It catalyzes collaborations resulting in open-source releases, standards contributions impacting IEEE Standards Association, and technology transfers to companies including ARM and Intel Corporation. Through interactions with conferences such as POPL (conference), PLDI (conference), and OOPSLA, the symposium shapes curriculum at institutions like University of Massachusetts Amherst and research agendas at funding bodies like NSF and European Commission.