8th WORKSHOP ON APPLICATIONS FOR MULTI-CORE ARCHITECTURESInternational audienceIn this paper, we analyse performance and energy consumption of four OpenMP runtime systems over a NUMA platform. We present an experimental study to characterize OpenMP runtime systems on the three main kernels in dense linear algebra algorithms (Cholesky, LU and QR) in terms of performance and energy consumption. Our experimental results suggest that OpenMP runtime systems can be considered as a new energy leverage. For instance, a LU factorization with concurrent write extension from libKOMP achieved up to 1.75 of performance gain and 1.56 of energy decrease
Near Threshold Voltage (NTV) computing has been recently proposed as a technique to save energy, at ...
[EN] In this paper, we propose a model for the energy consumption of the concurrent execution of thr...
OpenMP implementations must exploit current and upcoming hardware for performance. Overhead must be ...
8th WORKSHOP ON APPLICATIONS FOR MULTI-CORE ARCHITECTURESInternational audienceIn this paper, we ana...
This paper addresses the efficient exploitation of task-level parallelism, present in many dense lin...
In this paper we conduct a detailed analysis of the sources of power dissipation and energy consumpt...
This paper analyzes the impact on power consumption of two DVFS-control strategies when applied to t...
With the advent of multi-core technology, scientific and high performance computing research is beco...
The high performance computing (HPC) community is obsessed over the general matrix-matrix multiply (...
This dissertation incorporates two research projects: performance modeling and prediction for dense ...
In a previous PPoPP paper we showed how the FLAME method-ology, combined with the SuperMatrix runtim...
We investigate a parallelization strategy for dense matrix factorization (DMF) algorithms, using Ope...
The road towards Exascale Computing requires a holistic effort to address three different challenges...
In this thesis, the performance and energy efficiency of four different implementations of matrix mu...
The power wall asks for a holistic effort from the high performance and scientific communities to de...
Near Threshold Voltage (NTV) computing has been recently proposed as a technique to save energy, at ...
[EN] In this paper, we propose a model for the energy consumption of the concurrent execution of thr...
OpenMP implementations must exploit current and upcoming hardware for performance. Overhead must be ...
8th WORKSHOP ON APPLICATIONS FOR MULTI-CORE ARCHITECTURESInternational audienceIn this paper, we ana...
This paper addresses the efficient exploitation of task-level parallelism, present in many dense lin...
In this paper we conduct a detailed analysis of the sources of power dissipation and energy consumpt...
This paper analyzes the impact on power consumption of two DVFS-control strategies when applied to t...
With the advent of multi-core technology, scientific and high performance computing research is beco...
The high performance computing (HPC) community is obsessed over the general matrix-matrix multiply (...
This dissertation incorporates two research projects: performance modeling and prediction for dense ...
In a previous PPoPP paper we showed how the FLAME method-ology, combined with the SuperMatrix runtim...
We investigate a parallelization strategy for dense matrix factorization (DMF) algorithms, using Ope...
The road towards Exascale Computing requires a holistic effort to address three different challenges...
In this thesis, the performance and energy efficiency of four different implementations of matrix mu...
The power wall asks for a holistic effort from the high performance and scientific communities to de...
Near Threshold Voltage (NTV) computing has been recently proposed as a technique to save energy, at ...
[EN] In this paper, we propose a model for the energy consumption of the concurrent execution of thr...
OpenMP implementations must exploit current and upcoming hardware for performance. Overhead must be ...