44 citations · 93 across the 7 of their papers we have counts for
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cs.AR2022★ 44 cited
TAPA: A Scalable Task-Parallel Dataflow Programming Framework for Modern FPGAs with Co-Optimization of HLS and Physical Design
Licheng Guo, Yuze Chi, Jason Lau +9
In this paper, we propose TAPA, an end-to-end framework that compiles a C++ task-parallel dataflow program into a high-frequency FPGA accelerator. Compared to existing solutions, T…
cs.AR2022★ 12 cited
Callipepla: Stream Centric Instruction Set and Mixed Precision for Accelerating Conjugate Gradient Solver
Linghao Song, Licheng Guo, Suhail Basalama +3
The continued growth in the processing power of FPGAs coupled with high bandwidth memories (HBM), makes systems like the Xilinx U280 credible platforms for linear solvers which oft…
cs.AR2022
TopSort: A High-Performance Two-Phase Sorting Accelerator Optimized on HBM-based FPGAs
Weikang Qiao, Licheng Guo, Zhenman Fang +2
The emergence of high-bandwidth memory (HBM) brings new opportunities to boost the performance of sorting acceleration on FPGAs, which was conventionally bounded by the available o…