Implementation of the conjugate gradient algorithm on FPGA devices

Results of porting parts of the Lattice Quantum Chromodynamics code to modern FPGA devices are presented. A single-node, double precision implementation of the Conjugate Gradient algorithm is used to invert numerically the Dirac-Wilson operator on a 4-dimensional grid on a Xilinx Zynq evaluation board. The code is divided into two software/hardware parts in such a way that the entire multiplication by the Dirac operator is performed in programmable logic, and the rest of the algorithm runs on the ARM cores. Optimized data blocks are used to efficiently use data movement infrastructure allowing to reach intervals of 1 clock cycle. We show that the FPGA implementation can offer a comparable performance compared to that obtained using Intel Xeon Phi KNL.Comment: Proceedings of the 36th Annual International Symposium on Lattice Field Theory - LATTICE201

Towards Lattice Quantum Chromodynamics on FPGA devices

In this paper we describe a single-node, double precision Field Programmable Gate Array (FPGA) implementation of the Conjugate Gradient algorithm in the context of Lattice Quantum Chromodynamics. As a benchmark of our proposal we invert numerically the Dirac-Wilson operator on a 4-dimensional grid on three Xilinx hardware solutions: Zynq Ultrascale+ evaluation board, the Alveo U250 accelerator and the largest device available on the market, the VU13P device. In our implementation we separate software/hardware parts in such a way that the entire multiplication by the Dirac operator is performed in hardware, and the rest of the algorithm runs on the host. We find out that the FPGA implementation can offer a performance comparable with that obtained using current CPU or Intel's many core Xeon Phi accelerators. A possible multiple node FPGA-based system is discussed and we argue that power-efficient High Performance Computing (HPC) systems can be implemented using FPGA devices only.Comment: 17 pages, 4 figure

Implementation of the conjugate gradient algorithm in Lattice QCD on FPGA devices

Results of porting parts of the Lattice Quantum Chromodynamics code to modern FPGA devices are presented. A single-node, double precision implementation of the Conjugate Gradient algorithm is used to invert numerically the Dirac-Wilson operator on a 4-dimensional grid on a Xilinx Zynq evaluation board. The code is divided into two software/hardware parts in such a way that the entire multiplication by the Dirac operator is performed in programmable logic, and the rest of the algorithm runs on the ARM cores. Optimized data blocks are used to efficiently use data movement infrastructure allowing to reach intervals of 1 clock cycle. We show that the FPGA implementation can offer a comparable performance compared to that obtained using Intel Xeon Phi KN

An auction framework for DaaS in cloud computing and its evaluation

Data-as-a-service (DaaS) is the next emerging technology in cloud computing research. Small clouds operating as a group may exploit the DaaS efficiently to perform the substantial amount of work. In this paper, an auction framework is studied and evaluated when the small clouds are strategic in nature. We present the system model and formal definition of the problem and its experimental evaluation. Several auction DaaS-based mechanisms are proposed and their correctness and computational complexity is analysed. To the best of our knowledge, this is the first and realistic attempt to study the DaaS in a strategic setting. We have evaluated the proposed approach under various simulation scenarios to judge on its usefulness and efficiencyPeer ReviewedPostprint (author's final draft

Paralelismo aplicado a Ant Colony Optimization

La utilización de metaheurísticas para la resolución de problemas de optimización combinatoria del tipo NP-difícil ha permitido afrontar instancias grandes obteniendo soluciones cercanas al óptimo en tiempos razonables. En los últimos años la aplicación de paralelismo a las metaheurísticas ha demostrado su utilidad no solamente porque ha permitido disminuir considerablemente los tiempos de ejecución, sino también porque ha permitido obtener mejoras en la calidad de las soluciones encontradas. Ant Colony Optimization (ACO) es una metaheurística de las más recientes que ha sido aplicada con éxito sobre varios de los problemas estándares de optimización demostrando su potencial. Las primeras propuestas de paralelismo aplicado a ACO se remontan a los orígenes de la propia metaheurística. Sin embargo, la investigación en esta temática ha crecido notablemente en los últimos cinco años. El presente reporte es un relevamiento sobre la aplicación de técnicas de alto desempeño sobre ACO. El objetivo de este relevamiento es brindar un resumen de las principales propuestas existentes en la literatura sobre esta temática. Solamente se consideran las implementaciones paralelas aplicadas sobre problemas estáticos monobjetivos de optimización combinatoria

Self-Evaluation Applied Mathematics 2003-2008 University of Twente

This report contains the self-study for the research assessment of the Department of Applied Mathematics (AM) of the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at the University of Twente (UT). The report provides the information for the Research Assessment Committee for Applied Mathematics, dealing with mathematical sciences at the three universities of technology in the Netherlands. It describes the state of affairs pertaining to the period 1 January 2003 to 31 December 2008

Annual Report, 2013-2014

Beginning in 2004/2005- issued in online format onl