eProcessor: an open source full stack ecosystem

The project

The eProcessor project aims to build a new open source OoO processor and deliver the first completely open source European full-stack ecosystem based on this new RISC-V CPU.
The eProcessor 3-year project (1/4/21 - 31/3/24) aims to build a new open source OoO processor and deliver the first completely open source European full-stack ecosystem based on this new RISC-V CPU.

eProcessor technology will be extendable (open source), energy efficient (low power), extreme-scale (high performance), suitable for uses in HPC and embedded applications, and extensible (easy to add on-chip and/or off-chip components). 

The project is an ambitious combination of processor design, based on the RISC-V open source hardware ISA, applications and system software, bringing together multiple partners to leverage and extend pre-existing Intellectual Property (IP), combined with new IP that can be used as building blocks for future HPC systems, both for traditional and emerging application domains.

Objectives

The eProcessor project’s overall goal is to create an open source full stack ecosystem (both software and hardware) by achieving the following objectives:

  • Extend open source to include open source hardware for HPC.
  • Software/hardware co-design for improved application performance and system energy efficiency.
  • HPC and HPDA applications.
  • Focus on sustained application performance.
  • Stimulate European collaboration.
  • Combining industry standard methodology and cutting-edge research to accelerate exploitation.
  • Europe’s first Open Source high performance Out-of-Order (OOO) 64-bit RISC-V platform:
    • 4-way OOO Core
    • Single core & multi-core: 2 different chips
    • Multi-socket, cache coherent implementation
    • Adaptive caches
    • On chip Vector + AI accelerator
    • New Bioinformatics accelerator co-processor
    • Coherent off-chip accelerator: CNN

Applications

  • HPC:
  • Bioinformatics: FM-index, Smith-Waterman, Smith-Waterman-Gotoh, WFA.
  • AI applied to Bioinformatics: DeepHealth toolkit (EDDL+ECVL).
  • AI: Smart Mirror, Border Surveillance.

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