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Stephen Alan Herrod

dblp:69/2725 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 1995
—ORCID · none

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

Software engineering, systems software and programming languages · 2Systems, 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
2 papers
Performance modeling and evaluation · 44% Memory systems · 28% Parallel and multicore computing · 28%
Software engineering, system software, and programming languages
2 papers
Operating systems · 100%

Topics — the 6 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Memory systems
cache coherence
0.021995
Memory System Performance of UNIX on CC-NUMA Multiprocessors · SIGMETRICS 1995
The Impact of Architectural Trends on Operating System Performance · SOSP 1995
Operating systems
operating system performance
0.011995
The Impact of Architectural Trends on Operating System Performance · SOSP 1995
Parallel and multicore computing › task scheduling › dynamic scheduling
dynamically-scheduled processor
0.011995
The Impact of Architectural Trends on Operating System Performance · SOSP 1995
Performance modeling and evaluation › simulation › computer system simulation
machine simulation
0.011995
The Impact of Architectural Trends on Operating System Performance · SOSP 1995
Performance modeling and evaluation
simulation
0.011995
The Impact of Architectural Trends on Operating System Performance · SOSP 1995
Parallel and multicore computing
multiprocessor system
0.011995
The Impact of Architectural Trends on Operating System Performance · SOSP 1995

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

performance measurement · 0.0SimOS simulation · 0.0
YearPublicationVenuePosition
1995 Memory System Performance of UNIX on CC-NUMA Multiprocessors
John Chapin, Stephen Alan Herrod, Mendel Rosenblum, Anoop Gupta
SIGMETRICS2
1995 The Impact of Architectural Trends on Operating System Performance
abstract
Computer systems are rapidly changing.Over the next few years, we will see wide-scale deployment of dynamically-scheduled processors that can issue multiple instructions every clock cycle, execute instructions out of order, and overlap computation and cache misses.We also expect clock-rates to increase, caches to grow, and multiprocessors to replace uniprocessors.Using SimOS, a complete machine simulation environment, this paper explores the impact of the above architectural trends on operating system performance.We present results based on the execution of large and realistic workloads (program development, transaction processing, and engineering compute-server) running on the IRIX 5.3 operating system from Silicon Graphics Inc.Looking at uniprocessor trends, we find that disk 1/0 is the first-order bottleneck for workloads such as program development and transaction processing.Its importance continues to grow over time.Ignoring 1/0, we find that the memory system is the key bottleneck, stalling the CPU for over 50% of the execution time.Surprisingly, however, our results show that this stall fraction is unlikely to increase on future machines due to increased cache sizes and new latency hiding techniques in processors.We also find that the benefits of these architectural trends spread broadly across a majority of the important services provided by the operating system.We find the situation to be much worse for multiprocessors.Most operating systems services consume 3f)-i'0~0 more time than their uniprocessor counterparts.A large fraction of the stalls are due to coherence misses caused by communication between processors.Because larger caches do not reduce coherence misses, the performance gap between uniprocessor and multiprocessor performance will increase unless operating system developers focus on kernel restructuring to reduce unnecessary communication.The paper presents a detailed decomposition of execution time (e.g., instruction execution time, memory stall time separately for instructions and data, synchronization time) for important kernel services in the three workloads.
Mendel Rosenblum, Edouard Bugnion, Stephen Alan Herrod, Emmett Witchel, Anoop Gupta
SOSP3