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David A. Kramer

dblp:99/4566 · DBLP profile ↗
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3ranked-venue papers
1as first author
0since 2021 · last 2004
—ORCID · unresolved

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

Systems, architecture and hardware · 3 · 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
Distributed systems · 65% High-performance computing · 19% Parallel and multicore computing · 16%

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

TopicWeightPapersLastEvidence papers
Distributed systems
grid computing
0.012004
Utilization of a Local Grid of Mac OS X-Based Computers using Xgrid · HPDC 2004
High-performance computing
cluster computing
0.012004
Utilization of a Local Grid of Mac OS X-Based Computers using Xgrid · HPDC 2004
Parallel and multicore computing › parallel architecture
associative processor
0.011992
Bit-Parallel Arithmetic in a Massively-Parallel Associative Processor · IEEE Trans. Computers 1992
Parallel and multicore computing › parallel architecture
massively parallel processing
0.011992
Bit-Parallel Arithmetic in a Massively-Parallel Associative Processor · IEEE Trans. Computers 1992
YearPublicationVenuePosition
2004 Utilization of a Local Grid of Mac OS X-Based Computers using Xgrid
David A. Kramer, Matthew MacInnis
HPDC1
1992 Bit-Parallel Arithmetic in a Massively-Parallel Associative Processor
abstract
A simple but powerful architecture based on the classical associative processor model is proposed. By distributing logic among slices of storage cells such that a number of bit-planes share a simple logic unit, bit-parallel arithmetic for massively parallel processing becomes feasible. For m-bit operands, this architecture enables complex operations such as multiplication and division to execute in O(m) cycles as opposed to O(m/sup 2/) for bit-serial machines. Algorithms which utilize this bit-parallel property to efficiently perform operations on floating point data have been developed. The simplicity of the architecture enables its implementation using VLSI technology, and hence allows the construction of a word-parallel, bit-parallel, massively parallel (P/sup 3/) computing system. Implementations of the fast Fourier transform and matrix multiplication are presented to illustrate the operation of this system.>
Isaac D. Scherson, David A. Kramer, Brian D. Alleyne
IEEE Trans. Computers2
1990 A Fine-Grain Bit-Parallel, Word-Parallel, Massively-Parallel Associative Processor
Isaac D. Scherson, David A. Kramer, Brian D. Alleyne
ICPP (1)2