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Approximate trivial instructions

Published: 23 May 2020 Publication History

Editorial Notes

An erratum was issued for this paper on June 12, 2020. You can download the erratum from the supplemental material section of this citation page.

Abstract

Approximate computing has the potential to improve performance and energy efficiency in high-performance processors. This work focuses on the impact of approximating conventionally non-trivial instructions to trivial instructions. Instructions which do not need to be processed due to the nature of their operands, such as division by 1 or addition with 0 are trivial instructions. By approximating instructions which results in an acceptable level of accuracy in programs' outputs, we can increase the number of trivial instructions and enhance power and performance of trivial bypassing. To approximate integer values, we mask the least significant bits (LSBs) of instructions' operands. The number of masked bits is under the control of programmers. To approximate floating-point values, we propose two different schemes. The first scheme sets a threshold and approximates the values that lie within the threshold region. A 32- or 64-bit comparator, depending on the operand size, is used for comparison between the operand and the threshold. Thus, instructions which would have used the expensive floating-point units are bypassed and only a comparator and a few gates are used instead. The second scheme reduces cost of approximation by replacing full-blown comparators with smaller ones and performing inexact comparisons between the operand and the threshold. Our evaluations using a diverse set of benchmarks reveal that precise comparison and trivial bypassing improve energy-delay by 21% and 13%, respectively while the inexact approximation improves energy-delay by 22%.

Supplementary Material

p1-shaikh-erratum (p1-shaikh-erratum.pdf)
Erratum to "Approximate trivial instructions" by Shaikh et al., Proceedings of the 17th ACM International Conference on Computing Frontiers (CF '20).

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Cited By

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  • (2023)Mixed-Precision Architecture for GPU Tensor Cores2023 IEEE Smart World Congress (SWC)10.1109/SWC57546.2023.10448789(1-8)Online publication date: 28-Aug-2023
  • (2022)AxBy-ViT: Reconfigurable Approximate Computation Bypass for Vision Transformers2022 23rd International Symposium on Quality Electronic Design (ISQED)10.1109/ISQED54688.2022.9806143(1-5)Online publication date: 6-Apr-2022
  • (2021)Reducing Energy in GPGPUs through Approximate Trivial BypassingACM Transactions on Embedded Computing Systems10.1145/342944020:2(1-27)Online publication date: 4-Jan-2021

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cover image ACM Conferences
CF '20: Proceedings of the 17th ACM International Conference on Computing Frontiers
May 2020
298 pages
ISBN:9781450379564
DOI:10.1145/3387902
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 23 May 2020

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  1. approximate computing
  2. energy
  3. performance
  4. trivial instructions

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CF '20
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CF '20: Computing Frontiers Conference
May 11 - 13, 2020
Sicily, Catania, Italy

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Overall Acceptance Rate 273 of 785 submissions, 35%

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Cited By

View all
  • (2023)Mixed-Precision Architecture for GPU Tensor Cores2023 IEEE Smart World Congress (SWC)10.1109/SWC57546.2023.10448789(1-8)Online publication date: 28-Aug-2023
  • (2022)AxBy-ViT: Reconfigurable Approximate Computation Bypass for Vision Transformers2022 23rd International Symposium on Quality Electronic Design (ISQED)10.1109/ISQED54688.2022.9806143(1-5)Online publication date: 6-Apr-2022
  • (2021)Reducing Energy in GPGPUs through Approximate Trivial BypassingACM Transactions on Embedded Computing Systems10.1145/342944020:2(1-27)Online publication date: 4-Jan-2021

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