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Outlier detection is a data mining task consisting in the discovery of observations which deviate substantially from the rest of the data, and has many important practical applications. Outlier detection in very large data sets is however computationally very demanding and the size limit of the data that can be elaborated is considerably pushed forward by mixing three ingredients: efficient algorithms,...
The Texas Instruments (TI) C6678 “Shannon” is TI's most recently-released Digital Signal Processor (DSP). Although its original purpose was voice and video encoding and decoding, it may have the potential to become a practical coprocessor for scientific computing. In this paper, we evaluate the C6678 in terms of its programming methodology, performance, and power efficiency. As a case study, we implemented...
Exascale computing systems will require sufficient resilience to tolerate numerous types of hardware faults while still assuring correct program execution. Such extreme-scale machines are expected to be dominated by processors driven at lower voltages (near the minimum 0.5 volts for current transistors). At these voltage levels, the rate of transient errors increases dramatically due to the sensitivity...
The architecture of the latest Graphic Processing Unit (GPU) consists of a number of uniform programmable units integrated on the same chip, which facilitate the general-purpose computing beyond the graphic processing. With the multiple programmable units executing in parallel, the latest GPU shows superior performance for many non-graphic applications. Furthermore, programmers can have a direct control...
The computational power of modern graphics processing units (GPUs) has become an interesting alternative in high performance computing. The specialized hardware of GPUs delivers a high degree of parallelism and performance. Various applications in scientific computing have been implemented such that computationally intensive parts are executed on GPUs. In this article, we present a GPU implementation...
Recent years have seen the development of many new parallel extensions to high level languages. However, there does not yet seem to have been a concentrated effort to quantify their performance or qualify their usability. Toward this end, we have used several parallel extensions to implement four of the high performance computing (HPC) Challenge benchmarks-FFT, HPL, RandomAccess, and STREAM-according...
We explore the use of todaypsilas high-end graphics processing units on desktops to perform hierarchical agglomerative clustering with the compute unified device architecture - CUDA of NVIDIA. Although the advancement in graphics cards has made the gaming industry to flourish,there is a lot more to be gained the field of scientific computing, high performance computing and their applications. Previous...
Java is a valuable and emerging alternative for the development of parallel applications, thanks to the availability of several Java message-passing libraries and its full multithreading support. The combination of both shared and distributed memory programming is an interesting option for parallel programming multi-core systems. However, the concerns about Java performance are hindering its adoption...
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