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Grant: Discovery Grants Program - Individual

University of British Columbia

$65,000.00

Energy-Efficient Programmable Accelerators

EF 2017-18

Résumé
For 50 years computing systems have benefited from exponentially increasing performance per dollar. The first microprocessor was fabricated using 10 micrometer transistors in 1971 while recent designs have been manufactured using 14 nanometer transistors. The resulting five-orders of magnitude increase in transistor density combined with three orders of magnitude increase in clock frequency has enabled computing to change from handling only simple business calculations to supporting machine learning algorithms rivaling humans in accuracy and led to the emerging ""internet of things"" that promises to broadly increase convenience and productivity. However, the rate of transistor scaling will likely slow significantly after the 5nm process node threatening such visions for the future. Indeed, transistor threshold voltage scaling essentially stopped a decade ago resulting in stagnant clock frequencies, a shift to multicore and more recent concerns about ""dark silicon"". While alternative technologies (e.g., quantum computing) may provide excellent long term solutions these will take decades to fully develop resulting in a ""fallow period"" during which computing system capability will stagnate unless alternatives are found. In principle, computing system capability can be improved by orders of magnitude by exploiting specialized hardware. This promise comes at the expense of reduced flexibility and/or difficult programming models. The long-term goal of this research program is to enable order-of-magnitude improvements in computing capability per dollar versus today's computing hardware for diverse software applications. Such an improvement will almost certainly benefit business and society in general. For example, such increases could benefit society enabling more sophisticated machine learning to be applied embedded internet-of-things devices. An order of magnitude gain in computing capability could translate into the difference between a IoT enabled fridge that emails you if the milk is about to reach its use before date, and one that recognizes you are getting bored with your food choices and suggests a shopping list based upon past preferences and your family's health goals. This research program will tackle these goals by exploring both software and hardware approaches to improve the tradeoff between ease of software development and increasing computing capability by exploiting specialized hardware. The expected outcome is insights into how best to structure future computing systems so that the currently robust software industry remains viable past the end of Moore's Law. Canada will benefit because there is a growing number of computer hardware (Intel, AMD, Qualcomm) and software (Electronic Arts, IBM, Microsoft) companies with an RD presence here that can readily leverage these insights.
Programme
Discovery Grants Program - Individual
Emplacement
British Columbia, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data

Tel que publié

Application id
RGPIN-2016-05819
Name nom
Aamodt, Tor
Department département
Electrical and Computer Engineering - Electrical and Computer Engineering
Organization id
2
Institution établissement
University of British Columbia
Province en
British Columbia
Province fr
Colombie-Britannique
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2017
Competition year année de concours
2016
Award amount
65000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
Discovery grants programs
Group fr
Programmes de subventions à la découverte
Committee code
1510
Committee name en
Electrical and Computer Engineering
Committee name fr
Génie électrique et informatique
Area of application code
1200
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Advancement of knowledge
Area of application fr
Avancement des connaissances
Research subject code
2704
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Distributed and parallel processing
Research subject fr
Traitement réparti et simultané
Partie
2
Nb partie
5
Application title
Energy-Efficient Programmable Accelerators
Keyword
NSERC
Application summary
For 50 years computing systems have benefited from exponentially increasing performance per dollar. The first microprocessor was fabricated using 10 micrometer transistors in 1971 while recent designs have been manufactured using 14 nanometer transistors. The resulting five-orders of magnitude increase in transistor density combined with three orders of magnitude increase in clock frequency has enabled computing to change from handling only simple business calculations to supporting machine learning algorithms rivaling humans in accuracy and led to the emerging ""internet of things"" that promises to broadly increase convenience and productivity. However, the rate of transistor scaling will likely slow significantly after the 5nm process node threatening such visions for the future. Indeed, transistor threshold voltage scaling essentially stopped a decade ago resulting in stagnant clock frequencies, a shift to multicore and more recent concerns about ""dark silicon"". While alternative technologies (e.g., quantum computing) may provide excellent long term solutions these will take decades to fully develop resulting in a ""fallow period"" during which computing system capability will stagnate unless alternatives are found. In principle, computing system capability can be improved by orders of magnitude by exploiting specialized hardware. This promise comes at the expense of reduced flexibility and/or difficult programming models. The long-term goal of this research program is to enable order-of-magnitude improvements in computing capability per dollar versus today's computing hardware for diverse software applications. Such an improvement will almost certainly benefit business and society in general. For example, such increases could benefit society enabling more sophisticated machine learning to be applied embedded internet-of-things devices. An order of magnitude gain in computing capability could translate into the difference between a IoT enabled fridge that emails you if the milk is about to reach its use before date, and one that recognizes you are getting bored with your food choices and suggests a shopping list based upon past preferences and your family's health goals. This research program will tackle these goals by exploring both software and hardware approaches to improve the tradeoff between ease of software development and increasing computing capability by exploiting specialized hardware. The expected outcome is insights into how best to structure future computing systems so that the currently robust software industry remains viable past the end of Moore's Law. Canada will benefit because there is a growing number of computer hardware (Intel, AMD, Qualcomm) and software (Electronic Arts, IBM, Microsoft) companies with an RD presence here that can readily leverage these insights.