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9 results on '"Viñas Buceta, Moisés"'

1. Heterogeneous distributed computing based on high-level abstractions

Author

Viñas Buceta, Moisés, Fraguela, Basilio B., Andrade, Diego, Doallo, Ramón, Viñas Buceta, Moisés, Fraguela, Basilio B., Andrade, Diego, and Doallo, Ramón

Abstract

[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 memory systems, which require the usage of additional different programming paradigms and tools. In this paper, we propose a novel approach to program heterogeneous clusters that is based on high-level abstractions such as tiles and hierarchical decomposition combined with the powerful APIs that data types and embedded languages can provide in languages such as C++. Rather than building our proposal from scratch, we have implemented it as a natural integration of the existing Hierarchically Tiled Arrays (HTA) and Heterogeneous Programming Library (HPL) projects, ie, the first one being focused on distributed computing and the second one on heterogeneous processing. The result, called Heterogeneous Hierarchically Tiled Arrays (H2TA), is very intuitive and easy to use thanks to the global view of the data and the single-threaded view of the execution that it provides at cluster level together with the transparency it provides with respect to the management of the heterogeneous devices. An evaluation comparing our proposal with MPI-based implementations shows its large programmability advantages and the reasonable overhead incurred.

Published
2018

2. Facilitating the development of stencil applications using the Heterogeneous Programming Library

Author

Viñas Buceta, Moisés, Fraguela, Basilio B., Andrade, Diego, and Doallo, Ramón

Subjects
OpenCL, Programmability, Heterogeneity, Stencils, Shadow regions
Abstract

[Abstract] Stencil computations are very common in scientific codes. Heterogeneous systems achieve good results solving these problems, but their programming is complex because of the ghost regions required in multi-device implementations and the difficulty to properly exploit their hardware. The Heterogeneous Programming Library (HPL) is a recent framework that improves the programmability of heterogeneous devices. This paper describes two extensions of HPL focused on stencil computations. The first one allows to automatically update the ghost regions they involve. The second one automates the implementation of the computational kernels of these algorithms. In our evaluation, the first mechanism reduces on average the number of lines of code and the Halstead programming effort of the host code of comparable HPL baselines by 34% and 64.2%, respectively, while the second contribution reduces these metrics by 72% and 79% in the computational kernels, respectively. Also, the first technique has negligible performance overheads, while the second one matches the performance of manually developed kernels. As an added benefit, the facilitation of the development of these codes thanks to these techniques helps programmers experiment with optimizations suited for this applications such as the ghost cell expansion technique, which provides speedups of up to 13% in our experiments. Ministerio de Economía y Competitividad de España; TIN2013-42148-P Ministerio de Economía y Competitividad de España; TIN2016-75845-P Xunta de Galicia; ED431G/01

Published
2017

3. Improving the programmability of heterogeneous systems by means of libraries

Author

Viñas Buceta, Moisés, Andrade Canosa, Diego, Fraguela Rodríguez, Basilio B., and Universidade da Coruña. Departamento de Electrónica e Sistemas

Subjects
Paralelismo (Informática), Superinformática, Supercomputación
Abstract

Programa Oficial de Doutoramento en Investigación en Tecnoloxías da Información. 524V01, [Resumo] O emprego de dispositivos heteroxéneos coma co-procesadores en entornos de computación de altas prestacións (HPC) medrou ininterrompidamente nos últimos anos debido ás súas excelentes propiedades en termos de rendemento e consumo de enerx:ía. A ma.ior dispoñibilidade de sistemas HPC híbridos conlevou de forma natural a necesidade de desenrolar ferra.mentas de programación adecuadas para eles, sendo CUDA e OpenCL as máis a.mplamente empregadas na actualidade. Desafortunadamente, estas ferramentas son relativamente de baixo nivel, o cal emparellado co ma.ior número de detalles que deben de ser controlados cando se programan aceleradoras, fa.i da programación destes sistemas mediante elas, moito roáis complexa que a. programación tradicional de CPUs. Isto levou á. proposta de alternativas de roáis alto nivel para facilitar a programación de dispositivos heteroxéneos. Esta tesis contribúe neste campo presentando dúas libreríe., [Abstract] The usage of heterogeneous devices as co-processors in high performance computing (HPC) environments has steadily grown during the last years due to their excellent properties in terms of perfonnance and energy consumption. The larger a.vailability of hybrid HPC systems naturally led to the need to develop suitable programming tools for them, being the most widely tL'ied nowadays CUDA and OpenCL. Unfortlmatciy, these tools are relativcly low leve), which coupled with the large DUlllber of deta.ils that must be monaged when programming accelerators, makes the programm.ing of these systems using them much more complex thon that of trad.itional CPUs. This has led to the proposal of higher leve) alternatives that facilitate the progranuning of heterogeneous devices. This thesis contri bu tes to this field presenting two libraries that largely improve the programma.bility of heterogeneous systeins in C++, helping users to focus on what todo rather thtlJl onlow leve) tasks. These two libraries, the Heterogeneous Programming Library (HPL) and the Heterogeneous Hierarch.ically Tiled Arrays (H2TA), are well suited to nodes with one or more accelerators, a.nd to heterogeneous clusters, respectively. Both libraries have proveo to be able to incresse the productivity of the users improving the progro. mmability of their codes, and at the s8llle time, achieving performance similar to that of lower leve) solutions., [Resumen] El empleo de dispositivos heterogéneos como co-procesadores en entornos de computación de altas prestaciones (HPC) ha. crecido ininterrumpidamente durante los últimos años debido a. sus excelentes propiedades en términos de rendimiento y consumo de energía. La mayor disponibilidad de sistemas HPC híbridos conllevó de forma natural la necesidad de desarrollar herramientas de programación adecuadas para. ellos, siendo CUDA y OpenCL las más ampliamente utilizadas en la actualidad. Desafortunadamente, estas herramientas son relativamente de bajo nivel, lo cual emparejado con el mayor número de detalles que han de ser controlados cuando se programan aceleradoras, hacen de la programación de estos sistemas mediante ell8S mucho más compleja que la programación tradicional de CPUs. Esto ha llevado a la propuesta de alternativ8S de más alto nivel para facilitar la programación de dispositivos heterogéneos. Esta tesis contribuye a este campo presentando dos librerías que mejoran ampliamente la programabilidad de sistemas heterogéneos en C++, permitiendo a los usuarios centrarse en lo que hay que hacer en vez de en las tareas de bajo nivel. Nuestras propuestas, la librería Heterogeneous Progromming Librory (HPL) y la librería Heterogeneous Hierorchíoolly Tíled Arrays (H2TA), están diseñadas para nodos con una o más aceleradoras, y para clusters heterogéneos, respectivamente. Ambas librerías, han demostrado ser capaces de incrementar la productividad de los usuarios mejorando la programabilidad de sus códigos, y al mismo tiempo, lograr un rendimiento similar al de soluciones de más bajo nivel.

Published
2016

4. Improving the programmability of heterogeneous systems by means of libraries

Author

Andrade Canosa, Diego, Fraguela Rodríguez, Basilio B., Universidade da Coruña. Departamento de Electrónica e Sistemas, Viñas Buceta, Moisés, Andrade Canosa, Diego, Fraguela Rodríguez, Basilio B., Universidade da Coruña. Departamento de Electrónica e Sistemas, and Viñas Buceta, Moisés

Abstract

[Resumo] O emprego de dispositivos heteroxéneos coma co-procesadores en entornos de computación de altas prestacións (HPC) medrou ininterrompidamente nos últimos anos debido ás súas excelentes propiedades en termos de rendemento e consumo de enerx:ía. A ma.ior dispoñibilidade de sistemas HPC híbridos conlevou de forma natural a necesidade de desenrolar ferra.mentas de programación adecuadas para eles, sendo CUDA e OpenCL as máis a.mplamente empregadas na actualidade. Desafortunadamente, estas ferramentas son relativamente de baixo nivel, o cal emparellado co ma.ior número de detalles que deben de ser controlados cando se programan aceleradoras, fa.i da programación destes sistemas mediante elas, moito roáis complexa que a. programación tradicional de CPUs. Isto levou á. proposta de alternativas de roáis alto nivel para facilitar a programación de dispositivos heteroxéneos. Esta tesis contribúe neste campo presentando dúas libreríe.

Published
2016

5. High Productivity Multi-device Exploitation with the Heterogeneous Programming Library

Author

Viñas Buceta, Moisés, Fraguela, Basilio B., Andrade, Diego, Doallo, Ramón, Viñas Buceta, Moisés, Fraguela, Basilio B., Andrade, Diego, and Doallo, Ramón

Abstract

[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 kernel executions and, even worse, arrays portions that must be kept coherent among the di_erent device memories and the host memory. In addition, when devices with di_erent characteristics participate in a computation, optimally distributing the work among them is not trivial. In this paper we extend an existing framework for the programming of accelerators called Heterogeneous Programming Library (HPL) with three kinds of improvements that facilitate these tasks. The _rst two ones are the ability to de_ne subarrays and subkernels, which distribute kernels on di_erent devices. The last one is a convenient extension of the subkernel mechanism to distribute computations among heterogeneous devices seeking the best work balance among them. This last contribution includes two analytical models that have proved to automatically provide very good work distributions. Our experiments also show the large programmability advantages of our approach and the negligible overhead incurred.

Published
2016

6. Developing adaptive multi-device applications with the Heterogeneous Programming Library

Author

Viñas Buceta, Moisés, Bozkus, Zeki, Fraguela, Basilio B., Andrade, Diego, Doallo, Ramón, Viñas Buceta, Moisés, Bozkus, Zeki, Fraguela, Basilio B., Andrade, Diego, and Doallo, Ramón

Abstract

[Abstract] The usage of heterogeneous devices presents two main problems. One is their complex programming, a problem that grows when multiple devices are used. The second issue is that even if the codes for these devices can be portable on top of OpenCL, they lack performance portability, effectively requiring specialized implementations for each device to get good performance. In this paper we extend the Heterogeneous Programming Library (HPL), which improves the usability of heterogeneous systems on top of OpenCL, to better handle both issues. First, we provide HPL with mechanisms to support the implementation of any multi-device application that requires arbitrary patterns of communication between several devices and a host memory. In a second stage HPL is improved with an adaptive scheme to optimize communications between devices depending on the execution environment. An evaluation using benchmarks with very different nature shows that HPL reduces the SLOCs and programming effort of OpenCL applications by 27 and 43 %, respectively, while improving the performance of applications that exchange data between devices by 28 % on average.

Published
2015

7. A multi-GPU shallow-water simulation with transport of contaminants

Author

Viñas Buceta, Moisés, Lobeiras Blanco, Jacobo, Fraguela, Basilio B., Arenaz Silva, Manuel, Amor, Margarita, García, J.A., Castro, M.J., and Doallo, Ramón

Subjects
Ghost cell decoupling, Shallow water, CUDA, Finite volume methods, Multi-GPU, Recomputation, Pollutant transport
Abstract

[Abstract] This work presents cost-effective multi-graphics processing unit (GPU) parallel implementations of a finite-volume numerical scheme for solving pollutant transport problems in bidimensional domains. The fluid is modeled by 2D shallow-water equations, whereas the transport of pollutant is modeled by a transport equation. The 2D domain is discretized using a first-order Roe finite-volume scheme. Specifically, this paper presents multi-GPU implementations of both a solution that exploits recomputation on the GPU and an optimized solution that is based on a ghost cell decoupling approach. Our multi-GPU implementations have been optimized using nonblocking communications, overlapping communications and computations and the application of ghost cell expansion to minimize communications. The fastest one reached a speedup of 78 × using four GPUs on an InfiniBand network with respect to a parallel execution on a multicore CPU with six cores and two-way hyperthreading per core. Such performance, measured using a realistic problem, enabled the calculation of solutions not only in real time but also in orders of magnitude faster than the simulated time.Copyright © 2012 John Wiley & Sons, Ltd.

Published
2012

8. Parallelization of shallow water simulations on current multi-threaded systems

Author

Lobeiras Blanco, Jacobo, Viñas Buceta, Moisés, Amor, Margarita, Fraguela, Basilio B., Arenaz Silva, Manuel, García Rodríguez, José Antonio, Castro, M.J., Lobeiras Blanco, Jacobo, Viñas Buceta, Moisés, Amor, Margarita, Fraguela, Basilio B., Arenaz Silva, Manuel, García Rodríguez, José Antonio, and Castro, M.J.

Abstract

[Abstract]: In this work, several parallel implementations of a numerical model of pollutant transport on a shallow water system are presented. These parallel implementations are developed in two phases. First, the sequential code is rewritten to exploit the stream programming model. And second, the streamed code is targeted for current multi-threaded systems, in particular, multi-core CPUs and modern GPUs. The performance is evaluated on a multi-core CPU using OpenMP, and on a GPU using the streaming-oriented programming language Brook+, as well as the standard language for heterogeneous systems, OpenCL.

Published
2013

9. Exploiting Heterogeneous Parallelism With the Heterogeneous Programming Library

Author

Viñas Buceta, Moisés, Bozkus, Zeki, Fraguela, Basilio B., Viñas Buceta, Moisés, Bozkus, Zeki, and Fraguela, Basilio B.

Abstract

[Abstract] While recognition of the advantages of heterogeneous computing is steadily growing, the issues of programmability and portability hinder its exploitation. The introduction of the OpenCL standard was a major step forward in that it provides code portability, but its interface is even more complex than that of other approaches. In this paper, we present the Heterogeneous Programming Library (HPL), which permits the development of heterogeneous applications addressing both portability and programmability while not sacrificing high performance. This is achieved by means of an embedded language and data types provided by the library with which generic computations to be run in heterogeneous devices can be expressed. A comparison in terms of programmability and performance with OpenCL shows that both approaches offer very similar performance, while outlining the programmability advantages of HPL.

Published
2013

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