This study supports the use of the Companion as an aid in treatment of hypokinetic dysarthria in individuals with PD. Advantages and disadvantages of the Companion, as well as limitations of the present study and directions for future studies, are discussed.
Distributed shared memory (DSM) is an abstraction of shared memory on a distributed-memory machine. Hardware DSM systems support this abstraction at the architecture level; software DSM systems support the abstraction within the runtime system. One of the key problems in building an efficient software DSM system is to reduce the amount of communication needed to keep the distributed memories consistent. In this article we present four techniques for doing so: software release consistency; multiple consistency protocols; write-shared protocols; and an update-with-timeout mechanism. These techniques have been implemented in the Munin DSM system. We compare the performance of seven Munin application programs: first to their performance when implemented using message passing, and then to their performance when running on a conventional software DSM system that does not embody the preceding techniques. On a 16-processor cluster of workstations, Munin's performance is within 5% of message passing for four out of the seven applications. For the other three, performance is within 29 to 33%. Detailed analysis of two of these three applications indicates that the addition of a function-shipping capability would bring their performance to within 7% of the message-passing performance. Compared to a conventional DSM system, Munin achieves performance improvements ranging from a few to several hundred percent, depending on the application.
We are developing Munin y , a system that allows programs written for shared memory multiprocessors to be executed e ciently on distributed memory machines. Thus, Munin overcomes the architectural limitations of shared memory machines, while maintaining their advantages in terms of ease of programming. A unique characteristic of Munin is the mechanism by which the shared memory programming model is translated to the distributed memory hardware. This translation is performed by r u n time software, with the aid of semantic hints provided by the user. Each shared data object is supported by a memory coherence mechanism appropriate to the manner in which the object is accessed. This paper focuses on Munin's memory coherence mechanisms, and compares our approach to previous work in this area.
We are developing Munin, a system that allows programs written for shared memory multiprocessors to be executed efficiently on distributed memory machines. Munin attempts to overcome the architectural limitations of shared memory machines, while maintaining their advantages in terms of ease of programming. Our system is unique in its use of loosely coherent memory, based on the partial order specified by a shared memory parallel program, and in its use of type-specific memory coherence. Instead of a single memory coherence mechanism for all shared data objects, Munin employs several different mechanisms, each appropriate for a different class of shared data object. These type-specific mechanisms are part of a runtime system that accepts hints from the user or the compiler to determine the coherence mechanism to be used for each object. This paper focuses on the design and use of Munin's memory coherence mechanisms, and compares our approach to previous work in this area.t In Norse mythology, Munin (Memory) was one of two ravens perched on Odin's shoulder. Each day, Munin would fly across the world and bring back to Odin knowledge of man's memory. Thus, the raven Munin might be considered the world's first distributed shared memory mechanism.
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