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An FPGA-based supercomputer for statistical physics: The weird case of Janus

  • M. Baity-Jesi*
  • , R. A. Baños
  • , A. Cruz
  • , L. A. Fernandez
  • , J. M. Gil-Narvion
  • , A. Gordillo-Guerrero
  • , M. Guidetti
  • , D. Iñiguez
  • , A. Maiorano
  • , F. Mantovani
  • , E. Marinari
  • , V. Martin-Mayor
  • , J. Monforte-Garcia
  • , A. M͡noz Sudupe
  • , D. Navarro
  • , G. Parisi
  • , M. Pivanti
  • , S. Perez-Gaviro
  • , F. Ricci-Tersenghi
  • , J. J. Ruiz-Lorenzo
  • S. F. Schifano, B. Seoane, A. Tarancon, P. Tellez, R. Tripiccione, D. Yllanes
*Corresponding author for this work
  • Complutense University
  • University of Zaragoza
  • University of Extremadura
  • Aragonese Foundation for Research & Development
  • University of Rome La Sapienza
  • University of Ferrara

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

In this chapter we describe the Janus supercomputer, a massively parallel FPGA-based system optimized for the simulation of spin-glasses, theoretical models that describe the behavior of glassy materials. The custom architecture of Janus has been developed to meet the computational requirements of these models. Spin-glass simulations are performed using Monte Carlo methods that lead to algorithms characterized by (1) intrinsic parallelism allowing us to implement many Monte Carlo update engines within a single FPGA; (2) rather small data base (2 MByte) that can be stored on-chip, significantly boosting bandwidth and reducing latency. (3) need to generate a large number of good-quality long (≥ 32 bit) random numbers; (4) mostly integer arithmetic and bitwise logic operations. Careful tailoring of the architecture to the specific features of these algorithms has allowed us to embed up to 1024 special purpose cores within just one FPGA, so that simulations of systems that would take centuries on conventional architectures can be performed in just a few months.

Original languageEnglish
Title of host publicationHigh-Performance Computing Using FPGAs
PublisherSpringer New York
Pages481-506
Number of pages26
Volume9781461417910
ISBN (Electronic)9781461417910
ISBN (Print)1461417902, 9781461417903
DOIs
StatePublished - 1 Mar 2013
Externally publishedYes

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