Performance evaluation of the Orca shared-object system

Orca is a portable, object-based distributed shared memory (DSM) system. This article studies and evaluates the design choices made in the Orca system and compares Orca with other DSMs. The article gives a quantitative analysis of Orca's coherence protocol (based on write-updates with function...

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Bibliographic Details
Published in:ACM transactions on computer systems 1998-02, Vol.16 (1), p.1-40
Main Authors: Bal, Henri E., Bhoedjang, Raoul, Hofman, Rutger, Jacobs, Ceriel, Langendoen, Koen, Rühl, Tim, Kaashoek, M. Frans
Format: Article
Language:English
Subjects:
Applied sciences
Compilers
Computer design
Computer science
control theory
systems
Computer systems performance. Reliability
Computing methodologies
Concurrent programming languages
Distributed computing methodologies
Distributed programming languages
Evaluation
Exact sciences and technology
General programming languages
Language types
Parallel computing methodologies
Parallel processing
Parallel programming languages
Programming languages
Runtime environments
Software
Software and its engineering
Software notations and tools
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Summary:Orca is a portable, object-based distributed shared memory (DSM) system. This article studies and evaluates the design choices made in the Orca system and compares Orca with other DSMs. The article gives a quantitative analysis of Orca's coherence protocol (based on write-updates with function shipping), the totally ordered group communication protocol, the strategy for object placement, and the all-software, user-space architecture. Performance measurements for 10 parallel applications illustrate the trade-offs made in the design of Orca and show that essentially the right design decisions have been made. A write-update protocol with function shipping is effective for Orca, especially since it is used in combination with techniques that avoid replicating objects that have a low read/write ratio. The overhead of totally ordered group communication on application performance is low. The Orca system is able to make near-optimal decisions for object placement and replication. In addition, the article compares the performance of Orca with that of a page-based DSM (TreadMarks) and another object-based DSM (CRL). It also analyzes the communication overhead of the DSMs for several applications. All performance measurements are done on a 32-node Pentium Pro cluster with Myrinet and Fast Ethernet networks. The results show that Orca programs send fewer messages and less data than the TreadMarks and CRL programs and obtain better speedups.
ISSN:0734-2071
1557-7333
DOI:10.1145/273011.273014