NDLI: EnerJ:approximate data types for safe and general low-power computation

Content Provider	ACM Digital Library
Author	Grossman, Dan Ceze, Luis Fortuna, Emily Dietl, Werner Sampson, Adrian Gnanapragasam, Danushen
Abstract	Energy is increasingly a first-order concern in computer systems. Exploiting energy-accuracy trade-offs is an attractive choice in applications that can tolerate inaccuracies. Recent work has explored exposing this trade-off in programming models. A key challenge, though, is how to isolate parts of the program that must be precise from those that can be approximated so that a program functions correctly even as quality of service degrades. We propose using type qualifiers to declare data that may be subject to approximate computation. Using these types, the system automatically maps approximate variables to low-power storage, uses low-power operations, and even applies more energy-efficient algorithms provided by the programmer. In addition, the system can statically guarantee isolation of the precise program component from the approximate component. This allows a programmer to control explicitly how information flows from approximate data to precise data. Importantly, employing static analysis eliminates the need for dynamic checks, further improving energy savings. As a proof of concept, we develop EnerJ, an extension to Java that adds approximate data types. We also propose a hardware architecture that offers explicit approximate storage and computation. We port several applications to EnerJ and show that our extensions are expressive and effective; a small number of annotations lead to significant potential energy savings (10%-50%) at very little accuracy cost.
Starting Page	164
Ending Page	174
Page Count	11
File Format	PDF
ISSN	03621340 15581160
DOI	10.1145/1993316.1993518
Journal	ACM SIGPLAN Notices (SIGP)
Volume Number	46
Issue Number	6
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	1983-05-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Critical data Energy Power-aware computing Soft errors Accuracy-aware computing
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Software

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

EnerJ: approximate data types for safe and general low-power computation

Dynamic knobs for responsive power-aware computing (SIGP, Vol. 46, Issue. 3)

Flikker:saving DRAM refresh-power through critical data partitioning (SIGP, Vol. 46, Issue. 3)

Traceable data types for self-adjusting computation

Architecture support for disciplined approximate programming (SIGP, Vol. 47, Issue. 4)

Type-safe multithreading in cyclone

Ownership types for safe programming:preventing data races and deadlocks

Chisel:reliability- and accuracy-aware optimization of approximate computational kernels

Paraprox:pattern-based approximation for data parallel applications (SIGP, Vol. 49, Issue. 4)

EnerJ:approximate data types for safe and general low-power computation

Similar Documents

EnerJ: approximate data types for safe and general low-power computation

Dynamic knobs for responsive power-aware computing (SIGP, Vol. 46, Issue. 3)

Flikker:saving DRAM refresh-power through critical data partitioning (SIGP, Vol. 46, Issue. 3)

Traceable data types for self-adjusting computation

Architecture support for disciplined approximate programming (SIGP, Vol. 47, Issue. 4)

Type-safe multithreading in cyclone

Ownership types for safe programming:preventing data races and deadlocks

Chisel:reliability- and accuracy-aware optimization of approximate computational kernels

Paraprox:pattern-based approximation for data parallel applications (SIGP, Vol. 49, Issue. 4)

EnerJ:approximate data types for safe and general low-power computation