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Automatic Task Graph Generation Techniques
TLDR
We present a model of parallel computation, the parameterized task graph, which is a compact, problem size independent, representation of some frequently used directed acyclic task graphs. Expand
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Numerical Solution of Nonlinear Equations
TLDR
The numermal solutmn of n nonhnear equatmns in n varmbles using the methods of Newton, Brown, and Brent is drscussed. Expand
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Parallel algorithms and architectures
TLDR
Parallel Algorithms and Architectures provides a thorough introduction to this technology, explaining the fundamentals of parallelism in a logical and readable way. Expand
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Computability with Low-Dimensional Dynamical Systems
TLDR
In this paper, we show that similar systems in dimension two are also capable of universal computations. Expand
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The Komornik-Loreti Constant is Transcendental
Theorem [Komornik-Loretil. There exists a smallest q E (1, 2) for which there exists a unique expansion of 1 as 1 = ESn=j 8nq n with an E{, 11. Furthermore, for this smallest q, the coefficient 8n isExpand
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Parallel Gaussian elimination on an MIMD computer
TLDR
A graph-theoretic approach to analyse the performances of several parallel Gaussian-like triangularization algorithms on an MIMD computer. Expand
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Parallel QR decomposition of a rectangular matrix
SummaryWe show that the greedy algorithm introduced in [1] and [5] to perform the parallel QR decomposition of a dense rectangular matrix of sizem×n is optimal. Then we assume thatm/n2 tends to zeroExpand
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Complexity of parallel QR factorization
TLDR
An optimal algorithm to perform the parallel QR decomposition of a dense matrix of size <N</italic>, when an unlimited number of processors is available. Expand
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SLC: Symbolic scheduling for executing parameterized task graphs on multiprocessors
TLDR
We present a scheduling algorithm for a parameterized task graph which first derives symbolic linear clusters and assigns task clusters to processors in a multi-threaded fashion. Expand
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Compact DAG Representation and Its Dynamic Scheduling
TLDR
We propose a dynamic scheduling algorithm which finds good schedules for coarse-grain task graphs, has a low memory cost, and a low computational complexity. Expand
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