An Evaluation of the Amoeba Group Communication System

The Amoeba group communication system has two unique aspects: (1) it uses a sequencer-based protocol with negative acknowledgements for achieving a total order on all group messages; and (2) users choose the degree of fault tolerance they desire. This paper reports on our design decisions in retrospect, the performance of the Amoeba group system, and our experiences using the system. We conclude that sequencer-based group protocols achieve high performance (comparable to Amoeba's fast remote procedure call implementation), that the scalability of our sequencer-based protocols is limited by message processing time, and that the flexibility and modularity of user-level implementations of protocols is likely to outweigh the potential performance loss

Efficient Reliable Group Communication for Distributed Systems

Many applications can profit from broadcast communication, but few operating systems provide primitives that make broadcast communication available to user applications. In this paper we introduce primitives for broadcast communication that have been integrated with the Amoeba distributed operating system. The semantics of the broadcast primitives are simple, powerful, and easy to understand. Our primitives, for example, guarantee total ordering of broadcast messages. The proposed primitives are also efficient: if a network supports physical multicast, a reliable broadcast can be done in just slightly more than two messages on the average, so, the performance of a reliable broadcast is roughly comparable to that of a remote procedure call. In addition, the primitives are flexible: user applications can, for example, trade performance against fault tolerance. 1

Programming a Distributed System Using Shared Objects

Building the hardware for a high-performance distributed computer system is a lot easier than building its software. The authors describe a model for programming distributed systems based on abstract data types that can be replicated on all machines that need them. Read operations are done locally, without requiring network traffic. Writes can be done using a reliable broadcast algorithm if the hardware supports broadcasting; otherwise, a point-to-point protocol is used. The authors have built such a system based on the Amoeba microkernel, and implemented a language, Orca, on top of it. For Orca applications that have a high ratio of reads to writes, they measure good speedups on a system with 16 processors

Orca: A Language for Parallel Programming of Distributed Systems

Orca is a language for implementing parallel applications on loosely coupled distributed systems. Unlike most languages for distributed programming, it allows processes on different machines to share data. Such data are encapsulated in data-objects, which are instances of user-defined abstract data types. The implementation of Orca takes care of the physical distribution of objects among the local memories of the processors. In particular, an implementation may replicate and/or migrate objects in order to decrease access times to objects and increase parallelism. This paper gives a detailed description of the Orca language design and motivates the design choices. Orca is intended for applications programmers rather than systems programmers. This is reflected in its design goals to provide a simple, easy to use language that is type-secure and provides clean semantics. The paper discusses three example parallel applications in Orca, one of which is described in detail. It also describes..

Group Communication in Amoeba and its Applications

Unlike many other operating systems, Amoeba is a distributed operating system that provides group communication (i.e., one-to-many communication). We wil

Experience with Distributed Programming in Orca

Orca is a language for programming parallel applications on distributed computing systems. Although processors in such systems communicate only through message passing and not through shared memory, data types and create instances (objects) of these types, which may be shared among processes. All operations on shared objects are executed atomically. Orca’s shared objects are implemented by replicating them in the local memories of the proces-sors. Read operations use the local copies of the object, without doing any interprocess communication. Write operations update all copies using an efficient reliable broadcast protocol. In this paper, we briefly describe the language and its implementation and then report on our ex-periences in using Orca for three parallel applications: the Traveling Salesman Problem, the All-pairs Shortest Paths problem, and Successive Overrelaxation. These applications have different needs for shared data: TSP greatly benefits from the support for shared data; ASP benefits from the use of broad-cast communication, even though it is hidden in the implementation; SOR merely requires point-to-point communication, but still can be implemented in the language by simulating message passing

Parallel Programming Using Shared Objects and Broadcasting

The two major design approaches taken to build distributed and parallel computer systems, multiprocessing and multicomputing, are discussed. A model that combines the best properties of both multiprocessor and multicomputer systems, easy-to-build hardware, and a conceptually simple programming model is presented. Using this model, a programmer defines and invokes operations on shared objects, the runtime system handles reads and writes on these objects, and the reliable broadcast layer implements indivisible updates to objects using the sequencing protocol. The resulting system is easy to program, easy to build, and has acceptable performance on problems with a moderate grain size in which reads are much more common than writes. Orca, a procedural language whose sequential constructs are roughly similar to languages like C or Modula 2 but which also supports parallel processes and shared objects and has been used to develop applications for the prototype system, is described