Title :
Automatic generation of high throughput energy efficient streaming architectures for arbitrary fixed permutations
Author :
Ren Chen;Viktor K. Prasanna
Author_Institution :
Ming Hsieh Department of Electrical Engineering, University of Southern California, Los Angeles, USA 90089
Abstract :
Due to their high data-rate and simple control, streaming architectures have become popular for hardware implementation of data intensive applications. A key problem in designing such architectures is to permute streaming data. In this paper, we present a technique to realize arbitrary fixed permutation on streaming data. We develop a parameterized architecture which accepts data streams as input and generates the permuted data after a certain amount of delay. Our design accepts continuous input at a fixed rate of p per cycle, where p is the data parallelism of the architecture. To construct the streaming architecture for a given fixed permutation, we develop a mapping approach by configuring the classic Benes network to obtain the datapath and the control logic. We demonstrate a complete design automation tool which takes as input design parameters including the permutation pattern and the data parallelism p, and produces register-transfer level Verilog description of the design. We evaluate the generated designs on Xilinx Virtex-7 FPGA using post place-and-route results.
Conference_Titel :
Field Programmable Logic and Applications (FPL), 2015 25th International Conference on
DOI :
10.1109/FPL.2015.7293944