debouch
发表于 2025-3-28 18:32:03
Self-Organizing Hierarchical Cluster Timestampsally use vector timestamps to efficiently answer precedence queries. Many current vector-timestamp algorithms either have a poor time/space complexity tradeoff or are static. This limits the scalability of such observation tools. One algorithm, centralized hierarchical cluster timestamps, has potent
arabesque
发表于 2025-3-28 21:33:12
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剧本
发表于 2025-3-29 02:02:23
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FLUSH
发表于 2025-3-29 04:04:43
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官僚统治
发表于 2025-3-29 09:51:30
Checkpointing Facility on a Metasystemomputing, especially for process migration and recovery after system crash. This article describes the experiences on incorporating checkpointing and recovery facilities in a Java-based metasystem. Our case study is ., a metasystem for execution of Java byte-code, both sequential and parallel. This
简略
发表于 2025-3-29 14:23:32
Performance Evaluation and Prediction research investigation and a technological problem that requires innovations in tools and techniques to keep pace with system and application evolution. This dual view of performance “science” and performance “technology” jointly spans broad fields of performance modelling, evaluation, instrumentat
Infant
发表于 2025-3-29 17:30:34
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苦涩
发表于 2025-3-29 21:59:08
Performance Prediction of Oblivious BSP Programs mechanism, usually known as“oblivious synchronization” implies that different processors can be in different supersteps at the same time. An unwanted consequence of this software improvement is a loss of accuracy in prediction. This paper proposes an extension of the BSP complexity model to deal wi
秘方药
发表于 2025-3-30 00:05:46
Performance Prediction of Data-Dependent Task Parallel Programsand .. are either computationally complex or very inaccurate. In this paper we introduce an analytical approach based on the use of lambda distributions to approximate execution time distributions. This allows us to predict the first 4 statistical moments of . in terms of the first 4 moments of .. a
Allodynia
发表于 2025-3-30 04:33:06
The Tuning Problem on Pipelinesn pure theoretical analysis and in practical automatic profiling. Unfortunately, contributions in one area seem to ignore the results of the other.We introduce a general performance prediction methodology based on the integration of analytical models and profiling tools. According to this approach w