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handle: 11573/1682157
Scaling network packet processing performance to meet the in- creasing speed of network ports requires software programs to carefully leverage the network devices’ hardware features. This is a complex task for network programmers, who need to learn and deal with the heterogeneity of device architectures, and re-think their software to leverage them. In this paper we make first steps to reverse this design process, enabling the automatic generation of tailored hardware designs starting from a network packet processing program. We introduce eHDL, a high-level synthesis tool that automatically generates hardware pipelines from unmodified Linux’s eBPF/XDP programs. eHDL is designed to enable software developers to directly define and implement the hardware functions they need in the NIC. We prototype eHDL targeting a Xilinx Alveo U50 FPGA NIC, and evaluate it with a set of 5 eBPF/XDP programs. Our results show that the generated pipelines are efficient in terms of required hardware resources, using only 6.5%-13.3% of the FPGA, and always achieve the line rate forwarding throughput with about 1 microsecond of per-packet forwarding latency. Compared to other network-specific high-level synthesis tool, eHDL enables software programmers with no hardware expertise to describe stateful functions that operate on the entire packet data. Compared to alternative processor-based solutions that perform eBFP/XDP offloading to a NIC, eHDL provides 10-100x higher throughput.
Network Programming, HLS, ebpf smartnic FPGA, Hardware Offloading, eBPF, FPGA
Network Programming, HLS, ebpf smartnic FPGA, Hardware Offloading, eBPF, FPGA
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 12 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
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| downloads | 55 |

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