{"id":155111,"date":"1996-08-01T00:00:00","date_gmt":"1996-08-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/efficient-and-flexible-object-sharing\/"},"modified":"2018-10-16T21:51:27","modified_gmt":"2018-10-17T04:51:27","slug":"efficient-and-flexible-object-sharing","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/efficient-and-flexible-object-sharing\/","title":{"rendered":"Efficient and Flexible Object Sharing"},"content":{"rendered":"

DiSOM is a software-based distributed shared memory (DSM) system, which supports intra- and inter-application sharing in heterogeneous networks of multiprocessor workstations. Unlike previous DSM systems, DiSOM provides fine-grained control over communication while retaining a simple shared memory model. It achieves this by using an update-based implementation of entry consistency, semaphores, remote object invocation, dynamic decomposition of objects and object-oriented language mechanisms. These techniques allow programmers to exploit application-specific knowledge to improve performance. A comparison between DiSOM and TreadMarks, a state-of-the-art DSM system, shows that on average DiSOM executes 33% faster, and sends 69% fewer messages and 38% less data.<\/p>\n","protected":false},"excerpt":{"rendered":"

DiSOM is a software-based distributed shared memory (DSM) system, which supports intra- and inter-application sharing in heterogeneous networks of multiprocessor workstations. Unlike previous DSM systems, DiSOM provides fine-grained control over communication while retaining a simple shared memory model. It achieves this by using an update-based implementation of entry consistency, semaphores, remote object invocation, dynamic decomposition […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13563],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-155111","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-data-platform-analytics","msr-locale-en_us"],"msr_publishername":"","msr_edition":"Proceedings of the International Conference on Parallel Processing (ICPP'96), Proceedings 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