Issue |
EPJ Web of Conf.
Volume 295, 2024
26th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2023)
|
|
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Article Number | 10006 | |
Number of page(s) | 8 | |
Section | Exascale Science | |
DOI | https://doi.org/10.1051/epjconf/202429510006 | |
Published online | 06 May 2024 |
https://doi.org/10.1051/epjconf/202429510006
Outlines in hardware and software for new generations of exascale interconnects
1 Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Roma, Rome, Italy
2 Istituto Nazionale di Fisica Nucleare (INFN), Sezione di Roma Tor Vergata, Rome, Italy
* e-mail: michele.martinelli@roma1.infn.it
Published online: 6 May 2024
RED-SEA (https://redsea-project.eu/) is a European project funded in the framework of the H2020-JTI-EuroHPC-2019-1 call that started in April 2021. The goal of the project is to evaluate the architectural design of the main elements of the interconnection networks for the next generation of HPC systems supporting hundreds of thousands of computing nodes enabling the Exascale for HPC, HPDA and AI applications while providing preliminary prototypes.
The main technological feature is the BXI network, originally designed and produced by ATOS (France). The plan is to integrate in the next release of the network – BXI3 – the architectural solutions and novel IPs developed within the framework of the RED-SEA project.
The consortium is composed of 11 well-established research teams across Europe, with extensive experience in interconnects, including network design, deployment and evaluation.
Within RED-SEA, INFN is adopting a hardware/software co-design approach to design APEnetX, a scalable interconnect prototyped on latest generation Xilinx FPGAs, adding innovative components for the improvement of the performance and resiliency of the interconnect. APEnetX is an FPGA-based, PCIe Gen3/4 network interface card equipped with RDMA capabilities being the endpoint of a direct multidimensional toroidal network and suitable for integration in the BXI environment. APEnetX design will be benchmarked on project testbeds using real scientific applications like NEST, a spiking neural network simulator.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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