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James E. Mankovich

dblp:09/387 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 1998
—ORCID · none

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

Systems, architecture and hardware · 1Applied, interdisciplinary, general and emerging computing · 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.

Software engineering, system software, and programming languages
2 papers
Operating systems · 88% Compilers and program optimization · 12%
Computer architecture, parallel and distributed computing, and storage systems
2 papers
Parallel and multicore computing · 46% Distributed systems · 27% Embedded and real-time systems · 27%

Topics — the 7 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Operating systems
resource management
0.011998
A Dynamic Quality of Service Middleware Agent for Mediating Application Resource Usage · RTSS 1998
Distributed systems
middleware
0.011998
A Dynamic Quality of Service Middleware Agent for Mediating Application Resource Usage · RTSS 1998
Embedded and real-time systems
real-time scheduling
0.011998
A Dynamic Quality of Service Middleware Agent for Mediating Application Resource Usage · RTSS 1998
Parallel and multicore computing › multiprocessor system
shared-memory multiprocessor
0.011988
The convex C240 architecture · SC 1988
Parallel and multicore computing › multiprocessor system
tightly-coupled multiprocessor
0.011988
The convex C240 architecture · SC 1988
Compilers and program optimization › parallelization
automatic parallelization
0.011988
The convex C240 architecture · SC 1988
Compilers and program optimization
vectorization
0.011988
The convex C240 architecture · SC 1988

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

resource allocation algorithms · 0.0dynamic estimate refinement · 0.0automatic vectorization · 0.0automatic parallelization · 0.0
YearPublicationVenuePosition
1998 A Dynamic Quality of Service Middleware Agent for Mediating Application Resource Usage
abstract
High bandwidth applications with time-dependent resource requirements demand certain resource level assurances in order to operate correctly. Quality of service resource management techniques are being successfully developed that allow network systems to provide such assurances. These solutions generally assume that the operating system at either end of the network is capable of handling the throughput requirements of the applications. However, real operating systems have to manage many concurrent applications with varying resource requirements. Without specialized support, the operating system cannot guarantee the resources needed for any particular application. In support of these kinds of applications we have developed a middleware agent called a dynamic QoS manager (DQM) that mediates application resource usage so as to ensure that applications get the resources they need in order to provide adequate performance. The DQM employs a variety of algorithms to determine application resource allocations. Using application QoS levels, it provides for resource availability based algorithmic variation within applications and varying application periods. It also allows for inaccurate application resource usage estimates through a technique we have developed called dynamic estimate refinement. The paper discusses new developments in the design of the DQM and presents results showing DQM performance with both real and synthetic applications.
Scott A. Brandt, Gary J. Nutt, Toby S. Berk, James E. Mankovich
RTSS4
1988 The convex C240 architecture
abstract
A description is given of the C240, a tightly coupled, shared memory, parallel multiprocessor that supports up to 40-ns ECL/CMOS Cray-like processors. It is managed by a fully semaphored Unix operating system and can support up to 4 Gb of directly addressable physical memory. Convex proprietary compiler technology provides automatic vectorization and parallelization for Fortran, C and Ada. The allocation of parallel threads to physical processors is managed by ASAP (automatic self-allocating processors), which dynamically allocates and deallocates parallel threads to the processors.>
M. Chastain, G. Gostin, James E. Mankovich, Steven J. Wallach
SC3