ACCL+: an FPGA-Based Collective Engine for Distributed Applications
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Abstract (arXiv)
FPGAs are increasingly prevalent in cloud deployments, serving as Smart NICs or network-attached accelerators. Despite their potential, developing distributed FPGA-accelerated applications remains cumbersome due to the lack of appropriate infrastructure and communication abstractions. To facilitate the development of distributed applications with FPGAs, in this paper we propose ACCL+, an open-source versatile FPGA-based collective communication library. Portable across different platforms and supporting UDP, TCP, as well as RDMA, ACCL+ empowers FPGA applications to initiate direct FPGA-to-FPGA collective communication. Additionally, it can serve as a collective offload engine for CPU applications, freeing the CPU from networking tasks. It is user-extensible, allowing new collectives to be implemented and deployed without having to re-synthesize the FPGA circuit. We evaluated ACCL+ on an FPGA cluster with 100 Gb/s networking, comparing its performance against software MPI over RDMA. The results demonstrate ACCL+'s significant advantages for FPGA-based distributed applications and highly competitive performance for CPU applications. We showcase ACCL+'s dual role with two use cases: seamlessly integrating as a collective offload engine to distribute CPU-based vector-matrix multiplication, and serving as a crucial and efficient component in designing fully FPGA-based distributed deep-learning recommendation inference.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 10 of its 106 references that are in the map. First posted on arXiv 18 Dec 2023.
Builds on
10 of 106 references.
References · 10
- 2017Deep Interest Network for Click-Through Rate Predictioncited by 544
- 2019The Architectural Implications of Facebook's DNN-based Personalized Recommendationcited by 83
- 2020DeepRecSys: A System for Optimizing End-To-End At-scale Neural Recommendation Inferencecited by 54
- 2019TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learningcited by 43
- 2020Centaur: A Chiplet-based, Hybrid Sparse-Dense Accelerator for Personalized Recommendationscited by 21
- 2020Cross-Stack Workload Characterization of Deep Recommendation Systemscited by 11
- 2021Farview: Disaggregated Memory with Operator Off-loading for Database Enginescited by 3
- 2021Clio: A Hardware-Software Co-Designed Disaggregated Memory Systemcited by 3
- 2020A Survey of System Architectures and Techniques for FPGA Virtualizationcited by 2
- 2019Streaming Message Interface: High-Performance Distributed Memory Programming on Reconfigurable Hardwarecited by 1
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Citing papers per year: 2024: 1; 2025: 2.
3 papers.