OmpSs@cloudFPGA: An FPGA Task-Based Programming Model with Message Passing

Abstract

Nowadays, a new parallel paradigm for energyefficient heterogeneous hardware infrastructures is required to achieve better performance at a reasonable cost on highperformance computing applications. Under this new paradigm, some application parts are offloaded to specialized accelerators that run faster or are more energy-efficient than CPUs. Field-Programmable Gate Arrays (FPGA) are one of those types of accelerators that are becoming widely available in data centers.This paper proposes OmpSs@cloudFPGA, which includes novel extensions to parallel task-based programming models that enable easy and efficient programming of heterogeneous clusters with FPGAs. The programmer only needs to annotate, with OpenMP-like pragmas, the tasks of the application that should be accelerated in the cluster of FPGAs. Next, the proposed programming model framework automatically extracts parts annotated with High-Level Synthesis (HLS) pragmas and synthesizes them into hardware accelerator cores for FPGAs. Additionally, our extensions include and support two novel features: 1) FPGA-to-FPGA direct communication using a Message Passing Interface (MPI) similar Application Programming Interface (API) with one-to-one and collective communications to alleviate host communication channel bottleneck, and 2) creating and spawning work from inside the FPGAs to their own accelerator cores based on an MPI rank-like identification. These features break the classical host-accelerator model, where the host (typically the CPU) generates all the work and distributes it to each accelerator.We also present an evaluation of OmpSs@cloudFPGA for different parallel strategies of the N-Body application on the IBM cloudFPGA research platform. Results show that for cluster sizes up to 56 FPGAs, the performance scales linearly. To the best of our knowledge, this is the best performance obtained for N-body over FPGA platforms, reaching 344 Gpairs/s with 56 FPGAs. Finally, we compare the performance and power consumption of the proposed approach with the ones obtained by a classical execution on the MareNostrum 4 supercomputer, demonstrating that our FPGA approach reduces power consumption by an order of magnitude.

Corrections to “A Survey on FPGA-Based Heterogeneous Clusters Architectures”

“…In the 19th paragraph of subsection D ''General-Purpose Clusters'' of Section I ''Cluster Implementations,'' the third sentence should read ''A custom network interface (NI) in the FPGA provides support for all communications, allowing users to focus on their applications written on an OpenMP extension called OmpSs [3]. '' In the 8th paragraph of subsection C ''FPGAs in Data Centers'' of Section I ''Cluster Implementations,'' the penultimate sentence should read ''To further improve the usability of the platform, continuous developments have been made to integrate MPI [4], [5] and OmpSs [2] into the system. ''…”