Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/81245
Title: Performance comparison of single-precision SPICE Model-Evaluation on FPGA, GPU, Cell, and multi-core processors
Authors: Kapre, Nachiket
DeHon, Andre
Keywords: Computer Science and Engineering
Issue Date: 2009
Source: Kapre, N., & DeHon, A. (2009). Performance comparison of single-precision SPICE Model-Evaluation on FPGA, GPU, Cell, and multi-core processors. 2009 International Conference on Field Programmable Logic and Applications.
Conference: 2009 International Conference on Field Programmable Logic and Applications (FPL)
Abstract: Automated code generation and performance tuning techniques for concurrent architectures such as GPUs, Cell and FPGAs can provide integer factor speedups over multi-core processor organizations for data-parallel, floating-point computation in SPICE model-evaluation. Our Verilog AMS compiler produces code for parallel evaluation of non-linear circuit models suitable for use in SPICE simulations where the same model is evaluated several times for all the devices in the circuit. Our compiler uses architecture specific parallelization strategies (OpenMP for multi-core, PThreads for Cell, CUDA for GPU, statically scheduled VLIW for FPGA) when producing code for these different architectures. We automatically explore different implementation configurations (e.g. unroll factor, vector length) using our performance-tuner to identify the best possible configuration for each architecture. We demonstrate speedups of 3- 182times for a Xilinx Virtex5 LX 330T, 1.3-33times for an IBM Cell, and 3-131times for an NVIDIA 9600 GT GPU over a 3 GHz Intel Xeon 5160 implementation for a variety of single-precision device models.
URI: https://hdl.handle.net/10356/81245
http://hdl.handle.net/10220/39197
DOI: 10.1109/FPL.2009.5272548
Schools: School of Computer Engineering 
Rights: © 2009 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [http://dx.doi.org/10.1109/FPL.2009.5272548].
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Conference Papers

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