OffRAC: Offloading Through Remote Accelerator Calls
Fuente:
arXiv
Enregistré dans:
| Auteurs principaux: | , , , , , , |
|---|---|
| Format: | Preprint |
| Publié: |
2025
|
| Sujets: | |
| Accès en ligne: | |
| Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
| _version_ | 1866915233258274816 |
|---|---|
| author | Yang, Ziyi Iyer, Krishnan B. Chen, Yixi Shu, Ran István, Zsolt Canini, Marco Fahmy, Suhaib A. |
| author_facet | Yang, Ziyi Iyer, Krishnan B. Chen, Yixi Shu, Ran István, Zsolt Canini, Marco Fahmy, Suhaib A. |
| contents | Modern applications increasingly demand ultra-low latency for data processing, often facilitated by host-controlled accelerators like GPUs and FPGAs. However, significant delays result from host involvement in accessing accelerators. To address this limitation, we introduce a novel paradigm we call Offloading through Remote Accelerator Calls (OffRAC), which elevates accelerators to first-class compute resources. OffRAC enables direct calls to FPGA-based accelerators without host involvement. Utilizing the stateless function abstraction of serverless computing, with applications decomposed into simpler stateless functions, offloading promotes efficient acceleration and distribution of computational loads across the network. To realize this proposal, we present a prototype design and implementation of an OffRAC platform for FPGAs that assembles diverse requests from multiple clients into complete accelerator calls with multi-tenancy performance isolation. This design minimizes the implementation complexity for accelerator users while ensuring isolation and programmability. Results show that the OffRAC approach reduces the latency of network calls to accelerators down to approximately 10.5 us, as well as sustaining high application throughput up to 85Gbps, demonstrating scalability and efficiency, making it compelling for the next generation of low-latency applications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_04404 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | OffRAC: Offloading Through Remote Accelerator Calls Yang, Ziyi Iyer, Krishnan B. Chen, Yixi Shu, Ran István, Zsolt Canini, Marco Fahmy, Suhaib A. Networking and Internet Architecture Hardware Architecture Modern applications increasingly demand ultra-low latency for data processing, often facilitated by host-controlled accelerators like GPUs and FPGAs. However, significant delays result from host involvement in accessing accelerators. To address this limitation, we introduce a novel paradigm we call Offloading through Remote Accelerator Calls (OffRAC), which elevates accelerators to first-class compute resources. OffRAC enables direct calls to FPGA-based accelerators without host involvement. Utilizing the stateless function abstraction of serverless computing, with applications decomposed into simpler stateless functions, offloading promotes efficient acceleration and distribution of computational loads across the network. To realize this proposal, we present a prototype design and implementation of an OffRAC platform for FPGAs that assembles diverse requests from multiple clients into complete accelerator calls with multi-tenancy performance isolation. This design minimizes the implementation complexity for accelerator users while ensuring isolation and programmability. Results show that the OffRAC approach reduces the latency of network calls to accelerators down to approximately 10.5 us, as well as sustaining high application throughput up to 85Gbps, demonstrating scalability and efficiency, making it compelling for the next generation of low-latency applications. |
| title | OffRAC: Offloading Through Remote Accelerator Calls |
| topic | Networking and Internet Architecture Hardware Architecture |
| url | https://arxiv.org/abs/2504.04404 |