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Virantha N. Ekanayake

dblp:09/3049 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2004
—ORCID · none

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

Systems, architecture and hardware · 1 · 1 first-authorSoftware engineering, systems software and programming languages · 1 · 1 first-author

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
Embedded and real-time systems · 33% Energy-efficient computing · 33% Processor architecture and microarchitecture · 33%
Computer networks
1 paper
Internet of things and sensor networks · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Energy-efficient computing › energy management
low-power processor architecture
0.012004
An ultra low-power processor for sensor networks · ASPLOS 2004
Processor architecture and microarchitecture › instruction set architecture › RISC
RISC processor
0.012004
An ultra low-power processor for sensor networks · ASPLOS 2004
Embedded and real-time systems › wireless communication › wireless sensor networks
wireless sensor node
0.012004
An ultra low-power processor for sensor networks · ASPLOS 2004
Internet of things and sensor networks › wireless sensor network
energy-efficient computing
0.012004
An ultra low-power processor for sensor networks · ASPLOS 2004
Internet of things and sensor networks
wireless sensor network
0.012004
An ultra low-power processor for sensor networks · ASPLOS 2004

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

hardware event queue · 0.1event-driven architecture · 0.1
YearPublicationVenuePosition
2004 An ultra low-power processor for sensor networks
abstract
We present a novel processor architecture designed specifically for use in low-power wireless sensor-network nodes. Our sensor network asynchronous processor (SNAP/LE) is based on an asynchronous data-driven 16-bit RISC core with an extremely low-power idle state, and a wakeup response latency on the order of tens of nanoseconds. The processor instruction set is optimized for sensor-network applications, with support for event scheduling, pseudo-random number generation, bitfield operations, and radio/sensor interfaces. SNAP/LE has a hardware event queue and event coprocessors, which allow the processor to avoid the overhead of operating system software (such as task schedulers and external interrupt servicing), while still providing a straightforward programming interface to the designer. The processor can meet performance levels required for data monitoring applications while executing instructions with tens of picojoules of energy.We evaluate the energy consumption of SNAP/LE with several applications representative of the workload found in data-gathering wireless sensor networks. We compare our architecture and software against existing platforms for sensor networks, quantifying both the software and hardware benefits of our approach.
Virantha N. Ekanayake, Clinton Kelly IV, Rajit Manohar
ASPLOS1