The Impact of Hardware Gather/Scatter on Sparse Gaussian Elimination
نویسندگان
چکیده
Recent vector supercomputers provide vector memory access to "randomly" indexed vectors, whereas early vector supercomputers required contiguously or regularly indexed vectors. This additional capability, known as "hardware gather/scatter," can be used to great effect in general sparse Gaussian elimination. In this note we present some examples that show the impact of this change in hardware on the choice of algorithms for sparse Gaussian elimination. Common folk wisdom holds that general sparse Gaussian elimination algorithms do not perform well on vector computers. Our numerical results demonstrate that hardware gather/scatter allows general sparse elimination algorithms to outperform algorithms based on a band, envelope, or block structure on such computers.
منابع مشابه
Accelerating Magnetic Resonance Imaging through Compressed Sensing Theory in the Direction space-k
Magnetic Resonance Imaging (MRI) is a noninvasive imaging method widely used in medical diagnosis. Data in MRI are obtained line-by-line within the K-space, where there are usually a great number of such lines. For this reason, magnetic resonance imaging is slow. MRI can be accelerated through several methods such as parallel imaging and compressed sensing, where a fraction of the K-space lines...
متن کاملSpeech enhancement based on hidden Markov model using sparse code shrinkage
This paper presents a new hidden Markov model-based (HMM-based) speech enhancement framework based on the independent component analysis (ICA). We propose analytical procedures for training clean speech and noise models by the Baum re-estimation algorithm and present a Maximum a posterior (MAP) estimator based on Laplace-Gaussian (for clean speech and noise respectively) combination in the HMM ...
متن کاملSparse Gaussian Elimination on High Performance
Sparse Gaussian Elimination on High Performance Computers
متن کاملInvestigating the Effects of Hardware Parameters on Power Consumptions in SPMV Algorithms on Graphics Processing Units (GPUs)
Although Sparse matrix-vector multiplication (SPMVs) algorithms are simple, they include important parts of Linear Algebra algorithms in Mathematics and Physics areas. As these algorithms can be run in parallel, Graphics Processing Units (GPUs) has been considered as one of the best candidates to run these algorithms. In the recent years, power consumption has been considered as one of the metr...
متن کاملSparse Gaussian Elimination on High Performance Computers
Sparse Gaussian Elimination on High Performance Computers
متن کامل