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» Optimizing for parallelism and data locality
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CASES
2003
ACM
16 years 2 days 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 7 months 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
16 years 1 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,...
ICDAR
2003
IEEE
16 years 3 days 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...
PDCN
2004
15 years 8 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...