2005 6th International Conference on ASIC
DOI: 10.1109/icasic.2005.1611246
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An ASIC Design of a Novel Pipelined and Parallel Sorting Accelerator for a Multiprocessor-on-a-Chip

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Cited by 10 publications
(4 citation statements)
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“…However, the detriments include large numbers of processing elements (PE), high latency and the need to re-sort a full set of data upon a single new insertion. Martinez et al reduced sorting network latency by introducing levels of pipelining [4], while Tabrizi et al introduced a tree-like structure to reduce the area and PE complexity [5]. Nevertheless, sorting networks in general can not efficiently handle progressive incoming data, and their large area complexity may hinder implementation [6].…”
Section: A Sorting Networkmentioning
confidence: 99%
“…However, the detriments include large numbers of processing elements (PE), high latency and the need to re-sort a full set of data upon a single new insertion. Martinez et al reduced sorting network latency by introducing levels of pipelining [4], while Tabrizi et al introduced a tree-like structure to reduce the area and PE complexity [5]. Nevertheless, sorting networks in general can not efficiently handle progressive incoming data, and their large area complexity may hinder implementation [6].…”
Section: A Sorting Networkmentioning
confidence: 99%
“…They proposed a network that can sort any M input data that is smaller than N, which is the maximum number of data that the netwotk can sort. In their work [5] Tabrizi and Bagherzadeh use a different sorting scheme. Basically, they use a tree as a network implemented in an ASIC, where the leaves of the tree are the inputs and the main node is the output.…”
Section: Sorting Networkmentioning
confidence: 99%
“…However, the detriments include large numbers of processing elements (PE), high latency, and the need to resort a full set of data upon a single new insertion. Martínez et al reduced sorting network latency by introducing levels of pipelining [8], while Tabrizi and Bagherzadeh introduced a tree-like structure to reduce the area and PE complexity [9]. Nevertheless, sorting networks in general cannot efficiently handle progressive incoming data, and their large area and complexity may hinder implementation [10].…”
Section: Introductionmentioning
confidence: 99%