Kazuto Kubota

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We developed a compile-time metalevel architecture in C++, called the MPC ++ metalevel architecture , to not only extend and modify language semantics, but also extend syntax. This architecture overcomes the imperative languages' issue of compile-time metalevel processing. The proposed metalevel architecture has been implemented and tested. A typical(More)
We have built an eight node SMP cluster called COMPaS (Cluster Of Multi-Processor Systems), each node of which is a quad-processor Pentium Pro PC. We have designed and implemented a remote memory based user-level communication layer which provides low-overhead and high bandwidth using Myrinet. We designed a hybrid programming model in order to take(More)
Matrix clustering is a new data mining method which extracts a dense sub-matrix from a large sparse binary matrix. We propose an eecient algorithm named the ping-pong algorithm which enables real-time mining of a large sparse matrix. This article describes the application of matrix clustering to Web usage mining. Matrix clustering can be applied to Web(More)
NICAM is a communication layer for SMP PC clusters connected via Myrinet, designed to reduce overhead and latency by directly utilizing a microprocessor equipped on the network interface. It adopts remote memory operations to reduce much of the overhead found in message passing. NICAM employs an Active Messages framework for exibility in programming on the(More)
A new gridless router accelerated by Content Addressable Memory (CAM) is presented. A gridless version of the line-expansion algorithm is implemented, which always finds a path if one exists. The router runs in linear time by means of the CAM-based accelerator. Experimental results show that the more obstacles there are in the routing region, the more(More)
A simulation technique for very large-scale data parallel programs is proposed. In our simulation method, a data parallel program is divided into computation and communication sections. When the control ow of the parallel program does not depend on the contents of network messages, the computation time on each processor is calculated independently. An(More)
This paper proposes a parallel data-mining algorithm and its implementation on a PC cluster. The decision tree is a widely used data-mining algorithm for classifying records in a database. Simple parallelization of decision tree generation is not efficient because of the load imbalance caused by the form of the generated tree. The SPRINT algorithm solves(More)
Sequence pattern mining is one of the most important methods for mining WWW access log. The Apriori algorithm is well known as a typical algorithm for sequence pattern mining. However, it suffers from inherent difficulties in finding long sequential patterns and in extracting interesting patterns among a huge amount of results. This article proposes a new(More)
In this paper, we measure and compare the performance of shared-and distributed-memory multiproces-sors using a parallel tree search problem to characterize these types of multiprocessors. We take the knapsack problem using the branch-and-bound algorithm as our workload. It is dicult to compare the performance using irregular parallel problems such as tree(More)
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