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» Optimizing for parallelism and data locality
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118
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CASES
2003
ACM
15 years 6 months ago
Exploiting bank locality in multi-bank memories
Bank locality can be defined as localizing the number of load/store accesses to a small set of memory banks at a given time. An optimizing compiler can modify a given input code t...
Guilin Chen, Mahmut T. Kandemir, Hendra Saputra, M...
POPL
2007
ACM
16 years 29 days ago
Locality approximation using time
Reuse distance (i.e. LRU stack distance) precisely characterizes program locality and has been a basic tool for memory system research since the 1970s. However, the high cost of m...
Xipeng Shen, Jonathan Shaw, Brian Meeker, Chen Din...
IPPS
2007
IEEE
15 years 7 months ago
Self Adaptive Application Level Fault Tolerance for Parallel and Distributed Computing
Most application level fault tolerance schemes in literature are non-adaptive in the sense that the fault tolerance schemes incorporated in applications are usually designed witho...
Zizhong Chen, Ming Yang, Guillermo A. Francia III,...
98
Voted
ICDAR
2003
IEEE
15 years 6 months ago
A Low-Cost Parallel K-Means VQ Algorithm Using Cluster Computing
In this paper we propose a parallel approach for the Kmeans Vector Quantization (VQ) algorithm used in a twostage Hidden Markov Model (HMM)-based system for recognizing handwritte...
Alceu de Souza Britto Jr., Paulo Sergio Lopes de S...
111
Voted
PDCN
2004
15 years 2 months ago
K-Means VQ algorithm using a low-cost parallel cluster computing
It is well-known that the time and memory necessary to create a codebook from large training databases have hindered the vector quantization based systems for real applications. T...
Paulo Sergio Lopes de Souza, Alceu de Souza Britto...