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Toward efficient static analysis of finite-precision effects in DSP applications via affine arithmetic modeling
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Source Annual ACM IEEE Design Automation Conference archive
Proceedings of the 40th annual Design Automation Conference table of contents
Anaheim, CA, USA
SESSION: Novel techniques in high-level synthesis table of contents
Pages: 496 - 501  
Year of Publication: 2003
ISBN:1-58113-688-9
Authors
Claire Fang Fang  ECE, CMU
Rob A. Rutenbar  ECE, CMU
Markus Püschel  ECE, CMU
Tsuhan Chen  ECE, CMU
Sponsor
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 6,   Downloads (12 Months): 37,   Citation Count: 15
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ABSTRACT

We introduce a static error analysis technique, based on smart interval methods from affine arithmetic, to help designers translate DSP codes from full-precision floating-point to smaller finite-precision formats. The technique gives results for numerical error estimation comparable to detailed simulation, but achieves speedups of three orders of magnitude by avoiding actual bit-level simulation. We show results for experiments mapping common DSP transform algorithms to implementations using small custom floating point formats.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
L. H. de Figueiredo and J. Stolfi. Self-validated numerical methods and applications. Brazilian Mathematics Colloquium monograph, IMPA, Rio de Janeiro, Brazil, July 1997.
 
2
F. Fang, T. Chen, and R. Rutenbar. Floating-point bit-width optimization for low-power signal processing applications. In International Conf. on Acoustic, Speech, and Signal Processing, May 2002.
 
3
F. Fang, T. Chen, and R. Rutenbar. Lightweight floating-point arithmetic: Case study of inverse discrete cosine transform. EURASIP J. Sig. Proc.; Special Issue on Applied Implementation of DSP and Communication Systems, 2002(9):879--892, Sept. 2002.
 
4
 
5
T. L. Laakso and L. B. Jackson. Bounds for floating-point roundoff noise. IEEE Trans. Circ. Sys II: Analog and Digital Signal Processing, 41:424--426, June 1994.
6
 
7
B. Liu and T. Kaneko. Error analysis of digital filters realized with floating-point arithmetic. Proc. IEEE, 57:1735--1747, Oct. 1969.
 
8
R. E. Moore. Interval Analysis. Prentice-Hall, 1966.
 
9
 
10
B. D. Rao. Floating point arithmetic and digital filters. IEEE Trans. Sig. Proc., 40:85--95, Jan. 1992.
 
11
P. H. Sterbenz. Floating-Point Computation. Prentice-Hall, 1974.
 
12
C. Tsai. Floating-point roundoff noises of first- and second-order sections in parallel form digital filters. IEEE Trans. Circ. Sys II: Analog and Digital Signal Processing, 44:774--779, Sept. 1997.
 
13
C. Weinstein and A. V. Oppenheim. A comparison of roundoff noise in floating point and fixed point digital filter realizations. Proc. IEEE, 57:1181--1183, June 1969.

CITED BY  15

Collaborative Colleagues:
Claire Fang Fang: colleagues
Rob A. Rutenbar: colleagues
Markus Püschel: colleagues
Tsuhan Chen: colleagues