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- Thomas H. Cormen, Leonard F. Wisniewski
- SPAA
- 1993

We give asymptotically equal lower and upper bounds for the number of parallel 1/0 operations required to perform BMMC permutations (defined by a characteristic matrix that is nonsingular over GF(2)) on parallel disk systems. Under the Vitter-Shriver parallel-disk model with N records, D disks, block size B, and M records of RAM, we show a universal lower… (More)

We present the design and implementation of a parallel out-of-core sorting algorithm, which is based on Leighton's columnsort algorithm. We show how to relax some of the steps of the original columnsort algorithm to permit a faster out-of-core implementation. Our algorithm requires only 4 passes over the data, and a 3-pass implementation is possible.… (More)

The policies and mechanisms for migrating processes in a distributed system become more complicated in a heterogeneous environment, where the hosts may di er in their architecture and operating systems. These distributed systems include a large quantity and great diversity of resources which may not be fully utilized without the means to migrate processes… (More)

Current APIs for multiprocessor multi-disk le systems are not easy to use in developing out-of-core algorithms that choreograph parallel data accesses. Consequently, the e ciency of these algorithms is hard to achieve in practice. We address this de ciency by specifying an API that includes data-access primitives for data choreography. With our API, the… (More)

- Steven Abramson, William Horka, Leonard F. Wisniewski
- 2014 IEEE 34th International Conference on…
- 2014

Research computing in the social sciences requires access to statistical software and quantitative tools that perform embarrassingly parallel computation at moderate scale, large memory to fit entire data sets, and secure storage for potentially confidential data. The Research Computing Environment (RCE) was designed as a three-tier system to satisfy these… (More)

- Leonard F. Wisniewski
- IOPADS
- 1996

The ability to perform permutations of large data sets in place reduces the amount of necessary available disk storage. The simplest way to perform a permutation often is to read the records of a data set from a source portion of data storage, permute them in memory, and write them to a separate target portion of the same size. It can be quite expensive,… (More)

The fast cosine transform algorithms introduced in [ST91, Ste92] require fewer operations than any other known general algorithm. Similar to related fast transform algorithms (e.g., the FFT), these algorithms permute the data before, during, or after the computation of the transform. The choice of this permutation may be an important consideration in… (More)

- Terry Dontje, Don V. Kerr, +5 authors Leonard F. Wisniewski
- Parallel Tools Workshop
- 2008

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