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| Asia-Pacific Conference on Computer Systems | |
|---|---|
| Name | Asia-Pacific Conference on Computer Systems |
| Abbreviation | APCS |
| Discipline | Computer systems |
| Publisher | ACM SIGOPS / local hosts |
| Country | Various (Asia-Pacific) |
| First | 199x |
| Frequency | Annual / Biennial (varied) |
Asia-Pacific Conference on Computer Systems The Asia-Pacific Conference on Computer Systems is a regional scholarly conference focusing on computer systems research, bringing together researchers from institutions such as Massachusetts Institute of Technology, Stanford University, University of California, Berkeley, Tsinghua University, and National University of Singapore alongside industry participants from Google, Microsoft, Amazon, Tencent, and Alibaba Group. The conference serves as a forum for presentation and discussion of advances in operating systems, distributed systems, storage, networking, and benchmarking, attracting attendees from University of Cambridge, University of Oxford, University of Tokyo, Peking University, and Indian Institute of Technology campuses. Proceedings have been cited by work from ACM SIGCOMM, IEEE INFOCOM, USENIX, ACM SOSP, and ACM OSDI authors and are indexed in archival venues like ACM Digital Library and IEEE Xplore.
APCS typically features peer-reviewed technical papers, invited talks by faculty from Carnegie Mellon University, Princeton University, and Cornell University, tutorials led by researchers from ETH Zurich, EPFL, KAIST, and panels including representatives from Intel, AMD, ARM Holdings, NVIDIA, and IBM. The program often integrates workshops co-located with organizations such as ACM SIGPLAN, ACM SIGOPS, IEEE Computer Society, and regional bodies like Asia-Pacific Economic Cooperation panels. Awards at APCS have recognized contributors associated with prizes analogous to ACM Prize in Computing, Turing Award laureates, and recipients from institutions like Australian National University and University of Melbourne.
The conference lineage traces back to early regional workshops inspired by international meetings such as ACM/IEEE Supercomputing Conference and USENIX Annual Technical Conference, with early hosts including University of Hong Kong, National Taiwan University, and University of New South Wales. Over decades the event evolved from small colloquia linked to the Asia-Pacific Software Engineering Conference and International Conference on Distributed Computing Systems into a formal conference with peer review modeled after ACM SIGCOMM and IEEE INFOCOM processes. Notable historical editions were held in cities including Seoul, Beijing, Singapore, Sydney, and Tokyo, featuring keynote speakers from Microsoft Research, Google Research, IBM Research, and national labs such as Los Alamos National Laboratory and Lawrence Berkeley National Laboratory.
APCS covers topics comparable to those at ACM SOSP, ACM OSDI, and USENIX FAST, including operating systems research influenced by work at University of Illinois Urbana-Champaign and University of California, San Diego, distributed systems reflecting contributions from Yale University and Harvard University, storage systems inspired by NetApp and Seagate Technology, and networked systems connected to Cisco Systems and Juniper Networks. Other focal areas include cloud computing with ties to Amazon Web Services, virtualization research linked to VMware, edge computing resonant with Fog Computing initiatives, and security topics intersecting with research from MIT Lincoln Laboratory and SRI International.
Steering committees often include academics from National University of Singapore, Hong Kong University of Science and Technology, Indian Institute of Science, and Korea Advanced Institute of Science and Technology, and industry liaisons from Alibaba Cloud and Huawei. The governance model follows precedents set by ACM SIGPLAN and ACM SIGOPS with program committees drawn from faculty at Columbia University, University of Washington, Texas A&M University, Zhejiang University, and Fudan University. Local organizing committees coordinate logistics with regional partners such as Singapore University of Technology and Design and national research councils like Japan Society for the Promotion of Science and National Natural Science Foundation of China.
Proceedings are typically published in proceedings series supported by ACM Digital Library or local academic presses and sometimes indexed by IEEE Xplore and Scopus. Submissions undergo double‑blind or single‑blind peer review modeled on practices at ACM CHI and NeurIPS while adhering to policies similar to ICML and KDD regarding prior publication. Data and artifact evaluation tracks echo initiatives from ACM Artifact Review and Badging and reproducibility efforts at FAccT and USENIX ATC, encouraging authors to deposit datasets in repositories like Zenodo or institutional archives at Dryad (repository).
APCS has hosted influential papers later cited by researchers at Google DeepMind, Facebook AI Research, Microsoft Research Asia, and labs at Bell Labs. Topics with demonstrable impact include novel file systems inspired by work at Carnegie Mellon University and UC Berkeley, distributed consensus protocols influenced by Lamport, and network congestion control experiments building on research from Van Jacobson and S. Floyd schools. APCS papers have informed standards bodies such as IETF and IEEE 802 working groups and influenced deployments at hyperscale providers like Facebook and Google.
Past editions were hosted in collaboration with universities and cities such as Seoul, Beijing, Singapore, Sydney, Tokyo, Kuala Lumpur, Bangkok, Jakarta, and Taipei, with program committees including members from University of British Columbia and McGill University. Upcoming editions are typically announced by hosting institutions such as National University of Singapore or Tsinghua University and coordinated with sponsors including Asia Development Bank and corporate partners like Huawei and Tencent. Planned formats alternate between in-person sites and hybrid models influenced by pandemic-era events like NeurIPS 2020 and ICML 2020 adaptations.