We analyze the performance-power-energy balance of a conventional Intel Xeon mul- ticore processor and two low-power architectures –an Intel Atom processor and a sys- tem with a quad-core ARM Cortex A9+NVIDIA Quadro 1000M– using a high perfor- mance implementation of Gauss-Jordan elimination (GJE) for matrix inversion. The blocked version of this algorithm employed in the experimental evaluation mostly com- prises matrix-matrix products, so that the results from the evaluation carry beyond the simple matrix inversion and are representative for a wide variety of dense linear algebra operations/codes
The high performance computing community has traditionally focused uniquely on the reduction of exec...
In this work, we address the efficient realization of block-Jacobi preconditioning on graphics proce...
textIn the past, we could rely on technology scaling and new micro-architectural techniques to impro...
We analyze the performance-power-energy balance of a conventional Intel Xeon mul-ticore processor an...
The Gauss-Jordan Elimination scheme is an alternative to the LU decomposition for solving linear s...
In this paper, we tackle the inversion of large-scale dense matrices via conventional matrix factori...
We study the use of massively parallel architectures for computing a matrix inverse. Two different ...
Achieving high-performance while reducing power consumption is the key question as tech-nology scali...
In this paper we conduct a detailed analysis of the sources of power dissipation and energy consumpt...
This paper addresses the efficient exploitation of task-level parallelism, present in many dense lin...
This paper analyzes the impact on power consumption of two DVFS-control strategies when applied to t...
Matrix inversion is a mathematical algorithm that is widely used and applied in many real time engin...
Near Threshold Voltage (NTV) computing has been recently proposed as a technique to save energy, at ...
The performance of a parallel Gauss-Jordan matrix inversion algorithm on the Mark II hypercube3 at C...
The emergence of new manycore architectures, such as the Intel Xeon Phi, poses new challenges in how...
The high performance computing community has traditionally focused uniquely on the reduction of exec...
In this work, we address the efficient realization of block-Jacobi preconditioning on graphics proce...
textIn the past, we could rely on technology scaling and new micro-architectural techniques to impro...
We analyze the performance-power-energy balance of a conventional Intel Xeon mul-ticore processor an...
The Gauss-Jordan Elimination scheme is an alternative to the LU decomposition for solving linear s...
In this paper, we tackle the inversion of large-scale dense matrices via conventional matrix factori...
We study the use of massively parallel architectures for computing a matrix inverse. Two different ...
Achieving high-performance while reducing power consumption is the key question as tech-nology scali...
In this paper we conduct a detailed analysis of the sources of power dissipation and energy consumpt...
This paper addresses the efficient exploitation of task-level parallelism, present in many dense lin...
This paper analyzes the impact on power consumption of two DVFS-control strategies when applied to t...
Matrix inversion is a mathematical algorithm that is widely used and applied in many real time engin...
Near Threshold Voltage (NTV) computing has been recently proposed as a technique to save energy, at ...
The performance of a parallel Gauss-Jordan matrix inversion algorithm on the Mark II hypercube3 at C...
The emergence of new manycore architectures, such as the Intel Xeon Phi, poses new challenges in how...
The high performance computing community has traditionally focused uniquely on the reduction of exec...
In this work, we address the efficient realization of block-Jacobi preconditioning on graphics proce...
textIn the past, we could rely on technology scaling and new micro-architectural techniques to impro...