Processing in Memory: don't miss the first of our SRA white papers!


While preparing for the next edition of our Strategic Research Agenda (SRA), ETP4HPC is also working on a series of White Papers tackling technical issues pertaining to European HPC. "Processing in Memory: the Tipping Point" is the first of the series. So if you want to know why processing in memory is happening now and how to make it widely adopted in HPC, head for our webpage dedicated to the SRA white papers

Warm thanks to all authors, with a special mention for Paul and Petar who coordinated the team:

  • Petar Radojkovi?  (BSC)
  • Paul Carpenter (BSC)
  • Pouya Esmaili-Dokht (BSC)
  • Rémy Cimadomo (UPMEM)
  • Henri-Pierre Charles (CEA)
  • Abu Sebastian (IBM)
  • Paolo Amato (Micron) 

Decades after being initially explored in the 1970s, Processing in Memory (PIM) is currently experiencing a renaissance. By moving part of the computation to the memory devices, PIM addresses a fundamental issue in the design of modern computing systems, the mismatch between the von Neumann architecture and the requirements of important data-centric applications. A number of industrial prototypes and products are under development or already available in the marketplace, and these devices show the potential for cost-effective and energy-efficient acceleration of HPC, AI and data analytics workloads. This paper reviews the reasons for the renewed interest in PIM and surveys industrial prototypes and products, discussing their technological readiness. 

Wide adoption of PIM in production, however, depends on our ability to create an ecosystem to drive and coordinate innovations and co-design across the whole stack. European companies and research centres should be involved in all aspects, from technology, hardware, system software and programming environment, to updating of the algorithm and application. In this paper, we identify the main challenges that must be addressed and we provide guidelines to prioritise the research efforts and funding. We aim to help make PIM a reality in production HPC, AI and data analytics.

Note: the full collection of papers published by ETP4HPC is also available on the Zenodo open access repository, in the ETP4HPC community.

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