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Alex Bishara

dblp:20/9796 · DBLP profile ↗
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4ranked-venue papers
1as first author
0since 2021 · last 2015
—ORCID · none

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

Systems, architecture and hardware · 3Software engineering, systems software and programming languages · 1Applied, interdisciplinary, general and emerging computing · 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
2 papers
Processor architecture and microarchitecture · 42% Hardware accelerators and domain-specific architectures · 26% GPUs and heterogeneous computing · 15%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 9 heaviest of 9, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Hardware accelerators and domain-specific architectures
data-parallel accelerator
0.322013
Exploring the Tradeoffs between Programmability and Efficiency in Data-Parallel Accelerators · ACM Trans. Comput. Syst. 2013
Exploring the tradeoffs between programmability and efficiency in data-parallel accelerators · ISCA 2011
Processor architecture and microarchitecture › vector processor
vector-thread architecture
0.322013
Exploring the Tradeoffs between Programmability and Efficiency in Data-Parallel Accelerators · ACM Trans. Comput. Syst. 2013
Exploring the tradeoffs between programmability and efficiency in data-parallel accelerators · ISCA 2011
Bioinformatics and computational biology › genomics
genome sequencing
0.212015
Read Clouds Uncover Variation in Complex Regions of the Human Genome · RECOMB 2015
Bioinformatics and computational biology › genomics › structural variation
structural variation detection
0.212015
Read Clouds Uncover Variation in Complex Regions of the Human Genome · RECOMB 2015
Processor architecture and microarchitecture
SIMD
0.222013
Exploring the tradeoffs between programmability and efficiency in data-parallel accelerators · ISCA 2011
Exploring the Tradeoffs between Programmability and Efficiency in Data-Parallel Accelerators · ACM Trans. Comput. Syst. 2013
GPUs and heterogeneous computing › GPU microarchitecture
SIMT architecture
0.212013
Exploring the Tradeoffs between Programmability and Efficiency in Data-Parallel Accelerators · ACM Trans. Comput. Syst. 2013
Parallel and multicore computing › data parallelism
SIMD vectorization
0.112011
Exploring the tradeoffs between programmability and efficiency in data-parallel accelerators · ISCA 2011
Electronic design automation
design space exploration
0.012011
Exploring the tradeoffs between programmability and efficiency in data-parallel accelerators · ISCA 2011
Parallel and multicore computing › parallel architecture
MIMD architecture
0.012011
Exploring the tradeoffs between programmability and efficiency in data-parallel accelerators · ISCA 2011

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

VLSI implementation · 0.3read clouds · 0.2design space exploration · 0.2microbenchmarking · 0.1
YearPublicationVenuePosition
2015 Read Clouds Uncover Variation in Complex Regions of the Human Genome
Alex Bishara, Dorna Kashef Haghighi, Ziming Weng, Daniel E. Newburger, Robert B. West, Arend Sidow, Serafim Batzoglou
RECOMB1
2013 Exploring the Tradeoffs between Programmability and Efficiency in Data-Parallel Accelerators
abstract
We present a taxonomy and modular implementation approach for data-parallel accelerators, including the MIMD, vector-SIMD, subword-SIMD, SIMT, and vector-thread (VT) architectural design patterns. We introduce Maven, a new VT microarchitecture based on the traditional vector-SIMD microarchitecture, that is considerably simpler to implement and easier to program than previous VT designs. Using an extensive design-space exploration of full VLSI implementations of many accelerator design points, we evaluate the varying tradeoffs between programmability and implementation efficiency among the MIMD, vector-SIMD, and VT patterns on a workload of compiled microbenchmarks and application kernels. We find the vector cores provide greater efficiency than the MIMD cores, even on fairly irregular kernels. Our results suggest that the Maven VT microarchitecture is superior to the traditional vector-SIMD architecture, providing both greater efficiency and easier programmability.
Yunsup Lee, Rimas Avizienis, Alex Bishara, Richard Xia, Derek Lockhart, Christopher Batten, Krste Asanovic
ACM Trans. Comput. Syst.3
2011 The Maven vector-thread architecture
Yunsup Lee, Rimas Avizienis, Alex Bishara, Richard Xia, Derek Lockhart, Christopher Batten, Krste Asanovic
Hot Chips Symposium3
2011 Exploring the tradeoffs between programmability and efficiency in data-parallel accelerators
abstract
We present a taxonomy and modular implementation approach for data-parallel accelerators, including the MIMD, vector-SIMD, subword-SIMD, SIMT, and vector-thread (VT) architectural design patterns. We have developed a new VT microarchitecture, Maven, based on the traditional vector-SIMD microarchitecture that is considerably simpler to implement and easier to program than previous VT designs. Using an extensive design-space exploration of full VLSI implementations of many accelerator design points, we evaluate the varying tradeoffs between programmability and implementation efficiency among the MIMD, vector-SIMD, and VT patterns on a workload of microbenchmarks and compiled application kernels. We find the vector cores provide greater efficiency than the MIMD cores, even on fairly irregular kernels. Our results suggest that the Maven VT microarchitecture is superior to the traditional vector-SIMD architecture, providing both greater efficiency and easier programmability.
Yunsup Lee, Rimas Avizienis, Alex Bishara, Richard Xia, Derek Lockhart, Christopher Batten, Krste Asanovic
ISCA3