Zhijing George Mou. A formal model for divide-and-conquer and its parallel realization. Technical Report YALEU/DCS/RR-795, Department of Computer Science, Yale University, May 1990. Home/Search Document Not in Database Summary Related Articles Check |
This paper is cited in the following contexts:
Data Structures for Parallel Recursion - Kornerup (1997) (2 citations) (Correct)
....in this dissertation is that FP lists are linear, i.e. they are accessed using and . like 1 A Single Instruction Multiple Data (SIMD) 3 dimensional mesh architecture. 133 operators. Parallelism in FP is introduced by evaluating the second order functions in parallel. Mou and Hudak [MH88, Mou90] presented Divacon, a very general functional notation for describing divide and conquer programs. The Divacon notation is meant to capture the entire class of divide and conquer algorithms. The emphasis of their work is to implement divide and conquer descriptions efficiently on parallel ....
Zhijing G. Mou. A Formal Model for Divide-and-Conquer and Its Parallel Realization. PhD thesis, Department of Computer Science, Yale University, May 1990.
Compilation and Efficient Parallel Execution of Recursive Programs - Hänßgen (1994) (Correct)
....with future calls that cause thread migration to extract parallelism from a given program, preferably automatically. Their analysis technique in the compiler tries to find divide andconquer computation phases and exploit them accordingly. Finally, there is a divide and conquer algebra by [Mou90], who uses a functional parallel language to express problems such as reduction, communication, and Gaussian elimination. No larger problems are mentioned, and the efficient execution is limited to hypercube like networks. 5 Conclusion and future work We have shown the design of a system that can ....
Zhijing George Mou. A Formal Model for Divide-and-Conquer and Its Parallel Realization. PhD thesis, Yale University, May 1990.
A Simple Implementation of Divide and Conquer Parallelism.. - Roe (Correct)
....designing, writing and porting parallel programs is difficult. Data parallel programming is widely recognised as the simplest paradigm for parallel programming. Divide and conquer (D C) parallelism represents a particularly expressive form of data parallelism, which has been advocated by many [2, 3, 7 9]. This is more powerful than the simple data parallelism offered by Fortran 90 and C ; in particular it supports recursive parallel computation over arrays as advocated by Mou [8, 9] This enables basic operations such as scan and aggregation to be expressed. It also enables many other parallel ....
.... parallelism represents a particularly expressive form of data parallelism, which has been advocated by many [2, 3, 7 9] This is more powerful than the simple data parallelism offered by Fortran 90 and C ; in particular it supports recursive parallel computation over arrays as advocated by Mou [8, 9]. This enables basic operations such as scan and aggregation to be expressed. It also enables many other parallel algorithms to be expressed in a clear and succinct manner, for example: monotonic sort, matrix multiplication, polynomial evaluation, linear lower triangular systems, and Gaussian ....
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Z G Mou. A Formal Model for Divide-andConquer and Its Parallel Realization. Ph.D. thesis, Yale University, 1990.
Practical Parallel Divide-and-Conquer Algorithms - Hardwick (1997) (1 citation) (Correct)
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Zhijing George Mou. A formal model for divide-and-conquer and its parallel realization. Technical Report YALEU/DCS/RR-795, Department of Computer Science, Yale University, May 1990.
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