A Survey on the Shared Address Space with Privatized Static Variables (SAS-PSV) Execution Model for the Many-Core Era

  • Atsushi Hori
  • , Kaiming Ouyang
  • , Min Si
  • , Pavan Balaji
  • , Julien Jaeger
  • , Marc Pérache
  • , Sam White
  • , Evan Ramos Nvidia
  • , Laxmikant Kale
  • , Kevin Pedretti
  • , Ron Brightwell
  • , Balazs Gerofi
  • , Yutaka Ishikawa

Research output: Contribution to journalArticlepeer-review

Abstract

Parallel applications often use MPI processes and OpenMP threads. Those parallel execution models, multi-process and multi-thread, were invented to increase efficiency on uniprocessor systems. In the multi-process approach, each process’s isolated address space may make communication expensive; in the multi-thread design, shared variables may cause access conflicts and stall executions. Processes or threads interact and exchange information more often as CPU cores increase, and traditional execution models may create bottlenecks. The paradigm shift from uniprocessor to many-core systems necessitates the development of new parallel execution models to address challenges posed by the two parallel models. When processes share an address space, what happens? If threads don’t share static variables? Sharing an address space and privatizing static variables reduces information exchange and shared static variable exclusion costs. This survey investigates SAS-PSV (SAS-PSV), a new execution architecture that allows shared address space and static variable privatization. This notion is implemented by MPC, SMARTMAP, PVAS, PiP, and AMPI. Each has a different approach and execution. This article analyzes these implementations’ concepts, details, and hidden defects. We also present SAS-PSV applications and issues that need to be solved.

Original languageEnglish (US)
Article number3746169
JournalACM Computing Surveys
Volume58
Issue number1
Early online dateSep 2025
DOIs
StatePublished - Sep 1 2025

Keywords

  • Many core
  • MPI
  • multiple processes
  • multiple threads
  • OpenMP
  • parallel execution model

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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