Search arXiv⌕ Search

arXiv subjects

Andrea Motta

Publications and source records attributed to Andrea Motta.

2 recordsLinked to original sources

Toki: Profiling HBM Performance on FPGA Systems with RISC-V Soft Cores and PCIe Host DMA Traffic

Programmable RISC-V soft cores are becoming more widespread in data-center scenarios, making it crucial to design efficient systems that deploy them on FPGA chips with HBM memory. Toki, released as open source, is the first hardware-software framework that enables profiling the performance of HBM on FPGA accelerator cards by jointly considering (i) the execution of workloads on RISC-V soft cores instantiated on the FPGA and (ii) the injection of memory traffic from the host system via DMA over PCIe, providing insights that cannot be obtained with synthetic traffic generators alone. Extensive experiments target an AMD Alveo U55C card, deploying up to 60 RISC-V compute cores and stressing its HBM2 memory through real-world applications and microbenchmarks with user-defined access patterns. Results showcase how Toki can effectively profile the impact on HBM performance of the compute cores' organization, the workload's memory access patterns, data locality, contention over the memory controllers, and host traffic.

cs.AR↗

A Benchmarking Platform for DDR4 Memory Performance in Data-Center-Class FPGAs

FPGAs are increasingly utilized in data centers due to their capacity to exploit data parallelism in computationally intensive workloads. Furthermore, the processing of modern data center workloads requires moving vast amounts of data, making it essential to optimize data exchange between FPGAs and memory. This paper introduces a novel benchmarking platform for the evaluation of DDR4 memory performance in data-center-class FPGAs. The proposed solution features highly configurable traffic generation with complex memory access patterns defined at run time and can be flexibly instantiated on the target FPGA to support multiple memory channels and varying data rates. An extensive experimental campaign, targeting the AMD Kintex UltraScale 115 FPGA and encompassing up to three memory channels with data rates ranging from 1600 to 2400 MT/s and various memory traffic configurations, demonstrates the benchmarking platform's capability to effectively evaluate DDR4 memory performance.

cs.AR↗