NDLI: Approximate Computing: An Energy-Efficient Computing Technique for Error Resilient Applications

Content Provider	IEEE Xplore Digital Library
Author	Roy, K. Raghunathan, A.
Copyright Year	2015
Abstract	Approximate computing has become a well-known computing technique in recent years. It relies on the ability of many systems and applications to self-heal or to tolerate some loss of quality or optimality in the computed result. The main idea is to exploit the inherent error resiliency or error tolerance of the system to achieve energy efficiency, or in other words, trading accuracy with energy consumption. Such trade-off, in most cases, is also associated with performance improvements like faster operations, area reduction etc. Fortunately, most of the heavy workloads nowadays exhibit intrinsic application resilience. In most multimedia applications, the final output is interpreted by human senses, which are not perfect. This fact averts the need to produce exact outputs. Recent research efforts have quantitatively ascertained the high degree of inherent resilience in many applications. For example, our analysis of a benchmark suite of 12 recognition, vision and multimedia applications shows that on average, 83% of the runtime is spent in computations that can tolerate at least some degree of approximation. Therefore, there is a potential to leverage inherent resilience in a broad context. Let us consider digital signal processing (DSP). In multi-media applications, DSP blocks implement image, sound and video processing algorithms, where the final output is either an image or sound or a video for human senses. When interpreting an image or a sound or a video, human beings have limited perceptual capacities. This allows the system to be flexible in producing quality outputs. As an example, the relaxation on numerical precision provides some freedom to carry out imprecise or approximate computation. Another example of approximate signal processing is the utilization of incremental refinement. It is evident that the tradeoffs may allow approximate computing to handle tasks beyond what we can do with traditional computing.There are different levels of design abstraction where approximate computing methods can be implemented. In this paper we will briefly describe different approaches that we have developed to implement approximate hardware for error resilient applications.
Starting Page	473
Ending Page	475
File Size	116419
Page Count	3
File Format	PDF
e-ISBN	9781479987191
DOI	10.1109/ISVLSI.2015.130
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-08
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Approximation methods Energy efficiency Hardware Digital signal processing Computer architecture Discrete cosine transforms Resilience
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

IMPACT: IMPrecise adders for low-power approximate computing

Energy Efficient Approximate Arithmetic for Error Resilient Neuromorphic Computing

Energy scalable approximate DCT architecture trading quality via boundary error-resiliency

Approximate computing for efficient information processing

An efficient prime-factor algorithm for the discrete cosine transform and its hardware implementations

A Power Efficient Video Encoder Using Reconfigurable Approximate Arithmetic Units

Efficient formulation for the realization of discrete cosine transform using recursive structure

An efficient unified systolic architecture for the computation of discrete trigonometric transforms

New unified VLSI architectures for computing DFT and other transforms

Approximate Computing: An Energy-Efficient Computing Technique for Error Resilient Applications

Similar Documents

IMPACT: IMPrecise adders for low-power approximate computing

Energy Efficient Approximate Arithmetic for Error Resilient Neuromorphic Computing

Energy scalable approximate DCT architecture trading quality via boundary error-resiliency

Approximate computing for efficient information processing

An efficient prime-factor algorithm for the discrete cosine transform and its hardware implementations

A Power Efficient Video Encoder Using Reconfigurable Approximate Arithmetic Units

Efficient formulation for the realization of discrete cosine transform using recursive structure

An efficient unified systolic architecture for the computation of discrete trigonometric transforms

New unified VLSI architectures for computing DFT and other transforms

Approximate Computing: An Energy-Efficient Computing Technique for Error Resilient Applications