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In this paper we consider the k-clustering problem for n points in the d-dimensional space, motivated from the problem of computing a color lookup table for frame buer display, and that of compressing two-dimensional image data. Using the technique of computational geometry, this clustering problem is investigated in a unied manner.

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)

A novel data prefetching method -- access map pattern matching (AMPM) -- that uses "memory access map" is proposed. The AMPM prefetching concentrate hardware resources on collecting the access footprint of the frequently accessed area which we called "hot zones". 2-bit state is associated with each cache lines of hot zone. A set of these states is called… (More)

We present a novel approach to report approximate as well as exact k-closest pairs for sets of high dimensional points, under the L t-metric, t = 1; : : : ; 1. The proposed algorithms are eecient and simple to implement. They all use multiple shifted copies of the data points sorted according to their position along a space lling curve, such as the Peano… (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)

As the network speed grows, inter-layer coordination becomes more important. This paper shows 3 inter-layer coordination methods; (1) "Comet-TCP"; cooperation of data-link layer and transport layer using hardware, (2) "Transmission Rate Controlled TCP (TRC-TCP)"; cooperation of data-link layer and transport layer using software, and (3) "Dulling Edges of… (More)

End-to-end communications on 10 Gigabit Ethernet (10GbE) WAN became popular. However, there are difficulties that need to be solved before utilizing Long Fat-pipe Networks (LFNs) by using TCP. We observed that the followings caused performance depression: short-term bursty data transfer, mismatch between TCP and hardware support, and excess CPU load. In… (More)

This paper describes computational results for k-clustering algorithm using random sampling technique [2] to show its practical usefulness. By computational experiments, first, we show that small size of samples are actually enough for 2-clustering problem. Then, we apply this algorithm for k-clustering problem in a recursive manner and use the output as… (More)