Distributed programming with shared data

Bal, Henri E.; Tanenbaum, Andrew S.

doi:10.1016/0096-0551(91)90003-r

Cited by 30 publications

(17 citation statements)

References 30 publications

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“…Simply broadcasting all updates does not suffice, since update messages from different sources may arrive in different orders at the destination processors, resulting in inconsistencies [Bal and Tanenbaum 1988]. To solve this problem, the Orca system uses totally ordered group communication [Kaashoek 1992], which guarantees that all group messages are received by all processors in the same total order.…”

Section: Implementation Of Shared Objectsmentioning

confidence: 99%

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Performance evaluation of the Orca shared-object system

Bal

Bhoedjang

Hofman

et al. 1998

ACM Trans. Comput. Syst.

100

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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 the Orca programs send fewer messages and less data than the TreadMarks and CRL programs and obtain better speedups.

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Section: Implementation Of Shared Objectsmentioning

confidence: 99%

“…Orca's programming model was designed and implemented prior to most other DSM systems [Bal and Tanenbaum 1988] and differs from other DSM models by being object-based and language-based. Orca encapsulates shared data in objects and allows the programmer to define operations on objects, using abstract data types.…”

Section: Introductionmentioning

confidence: 99%

Performance evaluation of the Orca shared-object system

Bal

Bhoedjang

Hofman

et al. 1998

ACM Trans. Comput. Syst.

100

View full text Add to dashboard Cite

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“…These and other similar systems, and languages focus on object management and provide support for explicit management of object mobility. Other related work includes Distributed Smalltalk [8,9], Argus [39], Presto [10], Orca [6], Concurrent C++ [22], Avance [11] and Clouds [4]. A comparison of the relevant characteristics of the related programming languages are summarized in Table 1.…”

Section: Related Workmentioning

confidence: 99%

Language concepts using dynamic and distributed objects

George

1991

Proceedings of the 19th Annual Conference on Computer Science - CSC '91

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This paper presents the new concepts of static and dynamic objects in the context of an object-oriented parallel programming language. Examples are used to illustrate those concepts and their usefulness to practical software development. Dynamic objects provide an abstraction of objects similar to processes that move from one node to another in a distributed system, or airplanes that traverse the air-space controlled by different air-traffic control towers. Dynamic objects are semi-persistent entities because the life time of an object can be spanned by several objects which are active sequentially or in parallel. A relation, ownership, is defined between static and dynamic objects. Two programming language constructs export and import are defined to facilitate changes in the ownership relation. This imposes a new control flow among the objects and uses copy-and-delete semantics. The new constructs are illustrated using practical problems.

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“…This is a different approach than that used in object oriented systems such as [4,5,6,7] where each domain caches a copy of the objects that it is using. These systems are all designed around a particular object-based programming system that supports distributed programming.…”

Section: Introductionmentioning

confidence: 99%

Caching in an object oriented system

Nelson

Hamilton

Khalidi

Proceedings Third International Workshop on Object Orientation in Operating Systems

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Caching is an important technique for improving performance in distributed systems. However, in general it has been performed on an ad-hoc basis, with each component of the system having to invent its own caching techniques. In the Spring operating system we provide a unified caching architecture that can be used to cache a variety of aifferent kinds of remote objects. For any given kind of object, this architecture lets direrent client processes within a single machine share a single cache for accessing remote objects. This caching is performed by a separate cacher process on the machine local to client processes, the caching is transparent to the clients, and the cached information is kept coherent. This architecture has been used to implement caching for files and for naming contexts. IntroductionCaching of file and naming information has been used in operating systems for many years. It was originally used in timesharing systems to avoid disk operations (e.g. the UNIX@ operating system 111) and was later used in distributed systems to reduce network accesses and server loading (e.g. the Andrew [23 and Sprite [3] file systems). Measurements of distributed systems [2,3] have shown caching to be very effective in improving performance. In fact, in many cases caching can allow access to remote information to be as efficient as access to local information.This paper describes a general architecture for caching in Spring, a distributed operating system that is structured around the notion of objects. A Spring object is an abstraction that contains state and provides a set of operations to manipulate that state. Spring objects are implemented by domains which consist of an address space and a collection of threads; a domain in Spring is similar to a process on other systems such as the UNIX operating system. Objects can be freely passed between domains. Object invocations go to the implementor of the object which can be the same domain that is invoking the operation, another domain on the same machine, or a domain on a different machine.In Spring we use caching to improve the performance of operations on remotely implemented objects. Our goal is to make operations on remotely implemented objects as efficient as operations on locally implemented objects. In order to implement caching on Spring, we developed an architecture for caching that has several interesting features. First, the architecture is designed to be used to implement caching with coherency for many types of objects. This is important because new types of objects can be introduced into Spring at any time and we want to make the benefits of caching easily available to implementations of these new objects. This is a different approach from that taken in systems such as the UNIX and Sprite operating systems where the number of cacheable objects is fixed and no general caching architecture is available.The second interesting feature of the Spring caching architecture is that caching is performed by a separate cacher domain. This is a different approach than...

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Distributed programming with shared data

Cited by 30 publications

References 30 publications

Performance evaluation of the Orca shared-object system

Performance evaluation of the Orca shared-object system

Language concepts using dynamic and distributed objects

Caching in an object oriented system

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