Edgar Fabián Hernández-Ventura

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In the context of processing data lists in parallel in a multicore, various threads share a workload, each using a list to get and insert the data items to be processed; and when a list becomes empty, the owner thread steals data items from another list — thus balancing the workload according to the processing capacity of each thread transparently to the(More)
The Data List Management Library (DLML) processes data lists in parallel, balancing the workload transparently to programmers. Its first design was targeted at clusters of uniprocessor nodes, and based on multiprocess parallelism and on message-passing communication. This paper presents a multithreaded design of DLML aimed at clusters of multicore nodes to(More)
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