Impact Factor:2.8
DOI number:10.1109/TVLSI.2022.3151402
Journal:IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS
Place of Publication:美国
Key Words:Field-programmable gate array (FPGA), reconfigurable architecture, reconfigurable task, task placement algorithm.
Abstract:To date, only a tiny fraction of reconfigurable task placement algorithms is targeted at modern heterogeneous field-programmable gate array (FPGA) architecture, and they often focus on determining the final placement location and pursuing placement quality. Hence, their real-time performance is poor because feasible location searching and placement speed are rarely taken into consideration. In this article, we propose a fast search strategy based on characteristic target gene sequence (CTGS) and an efficient placement algorithm called prioritization-based minimum cost and marginal compact (P2MC). CTGS ascertains tasks’ feasible locations quickly by regarding the relatively few heterogeneous resources on FPGAs as search targets. P2MC first introduces prioritization heuristics based on task characteristics (PHTC) to presort tasks in order to improve the placement success rate and then select the final location according to the principle of minimum cost and marginal compact (2MC) so as to reduce the fragmentation of free space. The proposed algorithms are verified and evaluated on Xilinx’s mainstream FPGA families Virtex-5/6/7. Results show that CTGS can accelerate the search speed of tasks’ feasible locations
by about four to five times, and P2MC can further balance placement speed and success rate. Compared with state-of-theart heterogeneous task placement algorithms, P2MC can either increase both placement speed and success rate (by about 29% and 4.5%, respectively) or significantly increase the placement speed (by 20 times) at the expense of a bit of placement success rate (by only 5.8%).
Indexed by:Journal paper
Discipline:Engineering
Document Type:J
Volume:30
Issue:4
Page Number:474-487
Translation or Not:no
Date of Publication:2022-03-04
Included Journals:SCI
Date of Publication:2022-03-04