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In this paper we consider the k-clustering problem for a set S of n points p i = (x i) in the d-dimensional space with variance-based errors as clustering criteria, motivated from the color quantization problem of computing a color lookup table for frame buuer display. As the inter-cluster criterion to minimize, the sum of intra-cluster errors over every(More)
In this paper we consider the<italic>k</italic>-clustering problem for a set <italic>S</italic> of <italic>n</italic> points <inline-equation><f><inf>i</inf>=<fen lp="par"><b>x<inf>i</inf></b><rp post="par"> </fen></f> </inline-equation> in the<italic>d</italic>-dimensional space with variance-based errors as clustering criteria, motivated from the color(More)
We describe the GRAPE-DR (Greatly Reduced Array of Processor Elements with Data Reduction) system, which will consist of 4096 processor chips each with 512 cores operating at the clock frequency of 500 MHz. The peak speed of a processor chip is 512Gflops (single precision) or 256 Gflops (double precision). The GRAPE-DR chip works as an attached processor(More)
Data prefetching, advanced cache replacement policy, and memory access scheduling are incorporated in modern processors. Typically, each technique holds recently accessed locations independently and controls the memory subsystem based on the prediction of future memory access. Unfortunately, these specific optimizations often increase the implementation(More)
– Despite its simplicity and its linear time, a serial K-means algorithm's time complexity remains expensive when it is applied to a problem of large size of multidimensional vectors. In this paper we show an improvement by a factor of O(K/2), where K is the number of desired clusters, by applying theories of parallel computing to the algorithm. In addition(More)