Application-specific logic can be generated with a balance and mix of functional units tailored to match an application's computational requirements. The area and power consumption of application-specific functional units, registers and memory blocks is heavily dependent on the bit-widths of operands used in computations. The actual bit-width required to store the values assigned to a variable during execution of a program will not in general match the built-in C data types with fixed sizes of 8, 16, 32 and 64 bits. Thus, precious area is wasted if the built-in data type sizes are used to declare the size of operands. A novel stochastic bit-width approximation technique is introduced to estimate the required bit-width of integer variables using Extreme Value Theory. Results are presented to demonstrate reductions in bit-widths, area and power consumption when the probability of overflow/underflow occurring is varied from 0.1 to infinitesimal levels. Our experimental results show that the stochastic bit-width approximation results in overall 32% reduction in area and overall 21% reduction in the design power consumption on a FPGA chip for nine embedded benchmarks. © Springer-Verlag 2004.
CITATION STYLE
Özer, E., Nisbet, A. P., & Gregg, D. (2004). Stochastic bit-width approximation using extreme value theory for customizable processors. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2985, 250–264. https://doi.org/10.1007/978-3-540-24723-4_17
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