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Brian P. Wallenfelt

dblp:87/4503 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2006
—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
High-performance computing · 77% Distributed systems · 23%
Software engineering, system software, and programming languages
1 paper
Operating systems · 100%

Topics — the 1 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Operating systems › kernel
lightweight kernel
0.112006
Blue Gene system software - Designing a highly-scalable operating system: the Blue Gene/L story · SC 2006

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

linux port · 0.1compute node kernel · 0.1
YearPublicationVenuePosition
2006 Blue Gene system software - Designing a highly-scalable operating system: the Blue Gene/L story
abstract
Blue Gene/L is currently the world's fastest and most scalable supercomputer. It has demonstrated essentially linear scaling all the way to 131,072 processors in several benchmarks and real applications. The operating systems for the compute and I/O nodes of Blue Gene/L, are among the components responsible for that scalability. Compute nodes are dedicated to running application processes, whereas I/O nodes are dedicated to performing system functions. The operating systems adopted for each of these nodes reflect this separation of function. Compute nodes run a lightweight operating system called the compute node kernel. I/O nodes run a port of the Linux operating system. This paper discusses the architecture and design of this solution for Blue Gene/L in the context of the hardware characteristics that led to the design decisions. It also explains and demonstrates how those decisions are instrumental in achieving the performance and scalability for which Blue Gene/L is famous.
José E. Moreira, Michael Brutman, José G. Castaños, Thomas Engelsiepen, Mark Giampapa, Thomas Gooding, Roger L. Haskin, Todd Inglett, Derek Lieber, Patrick McCarthy, Michael B. Mundy, Jeff Parker, Brian P. Wallenfelt
SC13