Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Anuj Chandawalla

dblp:73/11096 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
0since 2021 · last 2012
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer architecture, parallel and distributed computing, and storage systems
1 paper
Energy-efficient computing · 61% Processor architecture and microarchitecture · 30% Embedded and real-time systems · 9%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Energy-efficient computing › power management › peak power management
computational sprinting
0.112012
Computational sprinting · HPCA 2012
Processor architecture and microarchitecture
multicore design
0.112012
Computational sprinting · HPCA 2012
Energy-efficient computing
thermal management
0.112012
Computational sprinting · HPCA 2012
Embedded and real-time systems › mobile computing
mobile computing platforms
0.012012
Computational sprinting · HPCA 2012

Methods — techniques the papers use, named apart from their topics

power budgeting · 0.1phase-change material thermal capacitance · 0.1
YearPublicationVenuePosition
2012 Computational sprinting
abstract
Although transistor density continues to increase, voltage scaling has stalled and thus power density is increasing each technology generation. Particularly in mobile devices, which have limited cooling options, these trends lead to a utilization wall in which sustained chip performance is limited primarily by power rather than area. However, many mobile applications do not demand sustained performance; rather they comprise short bursts of computation in response to sporadic user activity. To improve responsiveness for such applications, this paper explores activating otherwise powered-down cores for sub-second bursts of intense parallel computation. The approach exploits the concept of computational sprinting, in which a chip temporarily exceeds its sustainable thermal power budget to provide instantaneous throughput, after which the chip must return to nominal operation to cool down. To demonstrate the feasibility of this approach, we analyze the thermal and electrical characteristics of a smart-phone-like system that nominally operates a single core (~1W peak), but can sprint with up to 16 cores for hundreds of milliseconds. We describe a thermal design that incorporates phase-change materials to provide thermal capacitance to enable such sprints. We analyze image recognition kernels to show that parallel sprinting has the potential to achieve the task response time of a 16W chip within the thermal constraints of a 1W mobile platform.
Arun Raghavan, Anuj Chandawalla, Marios C. Papaefthymiou, Kevin P. Pipe, Thomas F. Wenisch, Milo M. K. Martin
HPCA3