Browsing ICC_Articles by Author "761c7969-3f7e-4a51-8ef1-61756cb7af22"
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A complete and efficient CUDA-sharing solution for HPC clusters
Elsevier (2014)In this paper we detail the key features, architectural design, and implementation of rCUDA, an advanced framework to enable remote and transparent GPGPU acceleration in HPC clusters. rCUDA allows decoupling GPUs from ... -
A parallel solver for huge dense linear systems
Elsevier (2011-11)HDSS (Huge Dense Linear System Solver) is a Fortran Application Programming Interface (API) to facilitate the parallel solution of very large dense systems to scientists and engineers. The API makes use of parallelism to ...
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A simulator to assess energy saving strategies and policies in HPC workloads
Association for Computing Machinery (ACM) (2012-07)In recent years power consumption of high performance computing (HPC) clusters has become a growing problem due, e.g., to the economic cost of electricity, the emission of car- bon dioxide (with negative impact on the ... -
A Survey on Malleability Solutions for High-Performance Distributed Computing
MDPI (2022-05-22)Maintaining a high rate of productivity, in terms of completed jobs per unit of time, in High-Performance Computing (HPC) facilities is a cornerstone in the next generation of exascale supercomputers. Process malleability ...
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Analysis of Threading Libraries for High Performance Computing
IEEE (2020-01-30)With the appearance of multi-many core machines, applications and runtime systems evolved in order to exploit the new on-node concurrency that brought new software paradigms. POSIX threads (Pthreads) was widely-adopted for ...
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Architecture-Aware Con guration and Scheduling of
Matrix Multiplication on
Asymmetric Multicore Processors
Springer US (2016-09)Asymmetric multicore processors (AMPs) have recently emerged as an appealing technology for severely energy-constrained environments, especially in mobile appliances where heterogeneity in applications is mainstream. ...
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Assessing Power Monitoring Approaches for Energy and Power Analysis of Computers
Elsevier (2014-06)Large-scale distributed systems (e.g., datacenters, HPC systems, clouds, large-scale networks, etc.) consume and will consume enormous amounts of energy. Therefore, accurately monitoring the power dissipation and energy ...
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Assessing the impact of the CPU power-saving modes on the task-parallel solution of sparse linear systems
Springer US (2014)We investigate the benefits that an energyaware implementation of the runtime in charge of the concurrent execution of ILUPACK —a sophisticated preconditioned iterative solver for sparse linear systems— produces on the ...
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Color and texture analysis using emerging parallel architectures
SAGE Publications (2011-11)While image texture is effective for use in pattern-recognition and image-analysis algorithms, textural features are time-consuming to calculate on standard CPUs. Therefore, we present novel implementations of textural-feature ...
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DMRlib: Easy-coding and Efficient Resource Management for Job Malleability
IEEE (2020-09-09)Process malleability has proved to have a highly positive impact on the resource utilization and global productivity in data centers compared with the conventional static resource allocation policy. However, the non-negligible ...
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DVFS-control techniques for dense linear algebra operations on multi-core processors
Springer (2012-11)This paper analyzes the impact on power consumption of two DVFS-control strategies when applied to the execution of dense linear algebra operations on multi-core processors. The strategies considered here, prototyped as ...
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Dynamic reconfiguration of noniterative scientific applications A case study with HPG aligner
Springer (2018-09)Several studies have proved the benefits of job malleability, that is, the capacity of an application to adapt its parallelism to a dynamically changing number of allocated processors. The most remarkable advantages of ...
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Energy-efficient execution of dense linear algebra algorithms on multi-core processors
Springer Verlag (2013-09)This paper addresses the efficient exploitation of task-level parallelism, present in many dense linear algebra operations, from the point of view of both computational performance and energy consumption. The strategies ...
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Enhancing performance and energy consumption of runtime schedulers for dense linear algebra
Wiley (2014-06)The road towards Exascale Computing requires a holistic effort to address three different challenges simultaneously: high performance, energy efficiency, and programmability. The use of runtime task schedulers to orchestrate ...
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Exploiting the capabilities of modern GPUs for dense matrix computations
John Wiley & Sons (2009)We present several algorithms to compute the solution of a linear system of equations on a graphics processor (GPU), as well as general techniques to improve their performance, such as padding and hybrid GPU-CPU computation. ...
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Exploring the interoperability of remote GPGPU virtualization using rCUDA and directive-based programming models
Springer (2016-06-21)Directive-based programming models, such as OpenMP, OpenACC, and OmpSs, enable users to accelerate applications by using coprocessors with little effort. These devices offer significant computing power, but their use can ...
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Extending OpenMP to Survive the Heterogeneous Multi-Core Era
Springer US (2010)This paper advances the state-of-the-art in programming models for exploiting task-level parallelism on heterogeneous many-core systems, presenting a number of extensions to the OpenMP language inspired in the StarSs ...
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GSaaS: A service to cloudify and schedule GPUs
IEEE (2018-07)Cloud technology is an attractive infrastructure solution that provides customers with an almost unlimited on-demand computational capacity using a pay-per-use approach, and allows data centers to increase their energy and ...
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Improving the user experience of the rCUDA remote GPU virtualization framework
Wiley (2014-10)Graphics processing units (GPUs) are being increasingly embraced by the high-performance computing community as an effective way to reduce execution time by accelerating parts of their applications. remote CUDA (rCUDA) was ...
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Large-scale linear system solver using secondary storage: self-energy in hybrid nanostructures
Elsevier (2011-02)We present a Fortran library which can be used to solve large-scale dense linear systems, Ax=b. The library is based on the LU decomposition included in the parallel linear algebra library PLAPACK and on its out-of-core ...
