research-article

Efficient floating point precision tuning for approximate computing

Authors:

Elavarasi Manogaran,

Asha AnooshehAuthors Info & Claims

2017 22nd Asia and South Pacific Design Automation Conference (ASP-DAC)

Pages 63 - 68

https://doi.org/10.1109/ASPDAC.2017.7858297

Published: 16 January 2017 Publication History

Abstract

This paper presents an automatic tool-chain that efficiently computes the precision of floating point variables down to the bit level of the mantissa. Our toolchain uses a distributed algorithm that can analyze thousands of variables. We successfully used the tool to transform floating point signal processing programs to their arbitrary precision fixed-point equivalent, obtaining about 82% and 66% average reduction in resources when compared to the double precision and single precision versions, respectively.

References

[1]

https://github.com/eliben/pycparser.

[2]

https://github.com/corvette-berkeley.

[3]

https://github.com/minhhn2910/fpprecisiontuning.

[4]

LogiCORE IP floating-point operator v7.0.

[5]

A. W. Brown, P. H. Kelly, and W. Luk. Profiling floating point value ranges for reconfigurable implementation. In Proceedings of the 1st HiPEAC Workshop on Reconfigurable Computing, pages 6–16, 2007.

[6]

I. Buck. nVidia's next-gen pascal gpu architecture to provide 10x speedup for deep learning apps., 2015.

[7]

M.-A. Cantin, Y. Savaria, and P. Lavoie. A comparison of automatic word length optimization procedures. In Circuits and Systems, 2002. ISCAS 2002. IEEE International Symposium on, volume 2, pages II-612. IEEE, 2002.

[8]

W.-F. Chiang, G. Gopalakrishnan, Z. Rakamaric, and A. Solovyev. Efficient search for inputs causing high floating-point errors. In ACM SIGPLAN Notices, volume 49, pages 43–52. ACM, 2014.

Digital Library

[9]

J. Chung and L.-W. Kim. Bit-width optimization by divide-and-conquer for fixed-point digital signal processing systems. Computers, IEEE Transactions on, 64(11): 3091–3101, 2015.

Digital Library

[10]

G. A. Constantinides, P. Y. Cheung, and W. Luk. Wordlength optimization for linear digital signal processing. Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on, 22(10): 1432–1442, 2003.

Digital Library

[11]

M. Courbariaux, Y. Bengio, and J.-P. David. Low precision arithmetic for deep learning. arXiv preprint arXiv:1412.7024, 2014.

[12]

F. De Dinechin, C. Lauter, and G. Melquiond. Certifying the floating-point implementation of an elementary function using Gappa. Computers, IEEE Transactions on, 60(2): 242–253, 2011.

Digital Library

[13]

F. De Dinechin and B. Pasca. Designing custom arithmetic data paths with flopoco. IEEE Design & Test of Computers, 4(28): 18–27, 2011.

[14]

L. Fousse, G. Hanrot, V. Lefevre, P. Pélissier, and P. Zimmermann. MPFR: A multiple-precision binary floating-point library with correct rounding. ACM Trans. Math. Softw., 33(2), June 2007.

Digital Library

[15]

A. A. Gaffar, O. Mencer, and W. Luk. Unifying bit-width optimisation for fixed-point and floating-point designs. In Field-Programmable Custom Computing Machines, 2004. FCCM 2004. 12th Annual IEEE Symposium on, pages 79–88. IEEE, 2004.

[16]

S. Gupta, A. Agrawal, K. Gopalakrishnan, and P. Narayanan. Deep learning with limited numerical precision. arXiv preprint arXiv:1502.02551, 2015.

[17]

N. Kapre and D. Ye GPU-accelerated high-level synthesis for bitwidth optimization of FPGA datapaths. In Proceedings of the 2016 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays, pages 185–194. ACM, 2016.

[18]

S. Kim, K.-I. Kum, and W. Sung. Fixed-point optimization utility for C and C++ based digital signal processing programs. Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on, 45(11): 1455–1464, 1998.

[19]

M. O. Lam, J. K. Hollingsworth, B. R. de Supinski, and M. P. LeGendre. Automatically adapting programs for mixed-precision floating-point computation. In Proceedings of the 27th international ACM conference on International conference on supercomputing, pages 369–378. ACM, 2013.

[20]

D.-U. Lee, A.A. Gaffar, R.C. Cheung, O. Mencer, W. Luk, G. Constantinides, et al. Accuracy-guaranteed bit-width optimization. Computer-Aided Design of Integrated Circuits and Systems, IEEE Transactions on, 25(10): 1990–2000, 2006.

Digital Library

[21]

D.-U. Lee, A.A. Gaffar, O. Mencer, and W. Luk. MiniBit: bit-width optimization via affine arithmetic. In Proceedings of the 42nd annual Design Automation Conference, pages 837–840. ACM, 2005.

[22]

C. Li, W. Luo, S. S. Sapatnekar, and J. Hu. Joint precision optimization and high level synthesis for approximate computing. In Proceedings of the 52nd Annual Design Automation Conference, page 104. ACM, 2015.

[23]

K. Nepal, Y. Li, R. Bahar, and S. Reda. Abacus: A technique for automated behavioral synthesis of approximate computing circuits. In Proceedings of the conference on Design, Automation & Test in Europe, page 361. European Design and Automation Association 2014.

[24]

C. Rubio-González, C. Nguyen, B. Mehne, K. Sen, J. Demmel, W. Kahan, C. Iancu, W. Lavrijsen, D. H. Bailey, and D. Hough. Floating-point precision tuning using blame analysis. In Proceedings of the 38th International Conference on Software Engineering, pages 1074–1085. ACM, 2016.

[25]

C. Rubio-González, C. Nguyen, H. D. Nguyen, J. Demmel, W. Kahan, K. Sen, D. H. Bailey, C. Iancu, and D. Hough. Precimonious: Tuning assistant for floating-point precision. In Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, page 27. ACM, 2013.

[26]

Q. Xu, T. Mytkowicz, and N. S. Kim. Approximate computing: A survey. IEEE Design & Test, 33(1): 8–22, 2016.

Cited By

Zoni DGalimberti A(2022)Cost-effective fixed-point hardware support for RISC-V embedded systemsJournal of Systems Architecture: the EUROMICRO Journal10.1016/j.sysarc.2022.102476126:COnline publication date: 23-May-2022
https://dl.acm.org/doi/10.1016/j.sysarc.2022.102476
Rabe RIzycheva ADarulova E(2021)Regime Inference for Sound Floating-Point OptimizationsACM Transactions on Embedded Computing Systems10.1145/347701220:5s(1-23)Online publication date: 17-Sep-2021
https://dl.acm.org/doi/10.1145/3477012

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Efficient floating point precision tuning for approximate computing
1. Software and its engineering

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cover image Guide Proceedings

2017 22nd Asia and South Pacific Design Automation Conference (ASP-DAC)

Jan 2017

786 pages

Copyright © 2017.

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IEEE Press

Publication History

Published: 16 January 2017

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Cited By

Zoni DGalimberti A(2022)Cost-effective fixed-point hardware support for RISC-V embedded systemsJournal of Systems Architecture: the EUROMICRO Journal10.1016/j.sysarc.2022.102476126:COnline publication date: 23-May-2022
https://dl.acm.org/doi/10.1016/j.sysarc.2022.102476
Rabe RIzycheva ADarulova E(2021)Regime Inference for Sound Floating-Point OptimizationsACM Transactions on Embedded Computing Systems10.1145/347701220:5s(1-23)Online publication date: 17-Sep-2021
https://dl.acm.org/doi/10.1145/3477012

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