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High Productivity Multi-device Exploitation with the Heterogeneous Programming Library
(Elsevier, 2016)
[Abstract] Heterogeneous devices require much more work from programmers than traditional CPUs, particularly when there are several of them, as each one has its own memory space. Multidevice applications require to distribute ...
Sparse Givens QR Factorization on a Multiprocessor
(IEEE Computer Society, 1996-06-01)
[Abstract]
We present a parallel algorithm for the QR factorization with column pivoting of a sparse matrix by means of Givens rotations. Nonzero elements of the matrix M to be decomposed are stored in a one dimensional ...
Parallel Sparse Modified Gram-Schmidt QR Decomposition
(Springer, 1996)
[Abstract] We present a parallel computational method for the QR decomposition with column pivoting of a sparse matrix by means of Modified Gram-Schmidt orthogonalization. Nonzero elements of the matrix M to be decomposed ...
Sparse Householder QR factorization on a mesh
(IEEE Computer Society, 1996-01)
[Abstract] We analyze the parallelization of QR factorization by means of Householder transformations. This parallelization is carried out on a machine with a mesh topology (a 2-D torus to be more precise). We use a cyclic ...
CPPC: a compiler‐assisted tool for portable checkpointing of message‐passing applications
(John Wiley & Sons Ltd., 2010-11-19)
[Abstract] With the evolution of high‐performance computing toward heterogeneous, massively parallel systems, parallel applications have developed new checkpoint and restart necessities. Whether due to a failure in the ...
Compiler-Assisted Checkpointing of Parallel Codes: The Cetus and LLVM Experience
(Springer New York LLC, 2013)
[Abstract] With the evolution of high-performance computing, parallel applications have developed an increasing necessity for fault tolerance, most commonly provided by checkpoint and restart techniques. Checkpointing tools ...
On processing extreme data
(Universitatea de Vest din Timisoara,West University of Timisoara, 2016)
[Abstract] Extreme Data is an incarnation of Big Data concept distinguished by the massive amounts of data that must be queried, communicated and analyzed in near real-time by using a very large number of memory or storage ...
An automatic optimizer for heterogeneous devices
(Elsevier, 2020-05)
[Abstract]: Codes written in a naive way seldom effectively exploit the computing resources, while writing optimized codes is usually a complex task that requires certain levels of expertise. This problem is further increased ...
Heterogeneous distributed computing based on high-level abstractions
(2018)
[Abstract]: The rise of heterogeneous systems has given place to great challenges for users as they involve new concepts, restrictions, and frameworks. Their exploitation is further complicated in the context of distributed ...
Guiding the Optimization of Parallel Codes on Multicores Using an Analytical Cache Model
(2018)
[Abstract]:
Cache performance is particularly hard to predict in modern multicore processors as several threads can be concurrently in execution, and private cache levels are combined with shared ones. This paper presents ...