328 research outputs found

    GPU-based Real-time Triggering in the NA62 Experiment

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    Over the last few years the GPGPU (General-Purpose computing on Graphics Processing Units) paradigm represented a remarkable development in the world of computing. Computing for High-Energy Physics is no exception: several works have demonstrated the effectiveness of the integration of GPU-based systems in high level trigger of different experiments. On the other hand the use of GPUs in the low level trigger systems, characterized by stringent real-time constraints, such as tight time budget and high throughput, poses several challenges. In this paper we focus on the low level trigger in the CERN NA62 experiment, investigating the use of real-time computing on GPUs in this synchronous system. Our approach aimed at harvesting the GPU computing power to build in real-time refined physics-related trigger primitives for the RICH detector, as the the knowledge of Cerenkov rings parameters allows to build stringent conditions for data selection at trigger level. Latencies of all components of the trigger chain have been analyzed, pointing out that networking is the most critical one. To keep the latency of data transfer task under control, we devised NaNet, an FPGA-based PCIe Network Interface Card (NIC) with GPUDirect capabilities. For the processing task, we developed specific multiple ring trigger algorithms to leverage the parallel architecture of GPUs and increase the processing throughput to keep up with the high event rate. Results obtained during the first months of 2016 NA62 run are presented and discussed

    Seeing Shapes in Clouds: On the Performance-Cost trade-off for Heterogeneous Infrastructure-as-a-Service

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    In the near future FPGAs will be available by the hour, however this new Infrastructure as a Service (IaaS) usage mode presents both an opportunity and a challenge: The opportunity is that programmers can potentially trade resources for performance on a much larger scale, for much shorter periods of time than before. The challenge is in finding and traversing the trade-off for heterogeneous IaaS that guarantees increased resources result in the greatest possible increased performance. Such a trade-off is Pareto optimal. The Pareto optimal trade-off for clusters of heterogeneous resources can be found by solving multiple, multi-objective optimisation problems, resulting in an optimal allocation of tasks to the available platforms. Solving these optimisation programs can be done using simple heuristic approaches or formal Mixed Integer Linear Programming (MILP) techniques. When pricing 128 financial options using a Monte Carlo algorithm upon a heterogeneous cluster of Multicore CPU, GPU and FPGA platforms, the MILP approach produces a trade-off that is up to 110% faster than a heuristic approach, and over 50% cheaper. These results suggest that high quality performance-resource trade-offs of heterogeneous IaaS are best realised through a formal optimisation approach.Comment: Presented at Second International Workshop on FPGAs for Software Programmers (FSP 2015) (arXiv:1508.06320

    Canadian Hydrogen Intensity Mapping Experiment (CHIME) Pathfinder

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    A pathfinder version of CHIME (the Canadian Hydrogen Intensity Mapping Experiment) is currently being commissioned at the Dominion Radio Astrophysical Observatory (DRAO) in Penticton, BC. The instrument is a hybrid cylindrical interferometer designed to measure the large scale neutral hydrogen power spectrum across the redshift range 0.8 to 2.5. The power spectrum will be used to measure the baryon acoustic oscillation (BAO) scale across this poorly probed redshift range where dark energy becomes a significant contributor to the evolution of the Universe. The instrument revives the cylinder design in radio astronomy with a wide field survey as a primary goal. Modern low-noise amplifiers and digital processing remove the necessity for the analog beamforming that characterized previous designs. The Pathfinder consists of two cylinders 37\,m long by 20\,m wide oriented north-south for a total collecting area of 1,500 square meters. The cylinders are stationary with no moving parts, and form a transit instrument with an instantaneous field of view of āˆ¼\sim100\,degrees by 1-2\,degrees. Each CHIME Pathfinder cylinder has a feedline with 64 dual polarization feeds placed every āˆ¼\sim30\,cm which Nyquist sample the north-south sky over much of the frequency band. The signals from each dual-polarization feed are independently amplified, filtered to 400-800\,MHz, and directly sampled at 800\,MSps using 8 bits. The correlator is an FX design, where the Fourier transform channelization is performed in FPGAs, which are interfaced to a set of GPUs that compute the correlation matrix. The CHIME Pathfinder is a 1/10th scale prototype version of CHIME and is designed to detect the BAO feature and constrain the distance-redshift relation.Comment: 20 pages, 12 figures. submitted to Proc. SPIE, Astronomical Telescopes + Instrumentation (2014

    Firmware and gateway for the ACE1 reconfigurable accelerator card

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    This thesis describes the continued work on the in-house designed FPGA based co-processor daughtercard referred to as ACE1. The aim: to create an ecosystem incorporating firmware, bootstrapping code, drivers and a development environment to create a seamless environment. Challenges in setting up and debugging the interface that connects the coprocessor daughtercard to the host server include: problems with the power network, the edge connectors and timing problems with the primary protocol which prevented host-based communications. The options include allowing the daughtercard to function in a stand-alone fashion and we present a gateware solution that allows users to select from a number of alternatives for each of the layers in the Open Systems Interconnect networking model

    Virtualized FPGA accelerators for efficient cloud computing

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    Hardware accelerators implement custom architectures to significantly speed up computations in a wide range of domains. As performance scaling in server-class CPUs slows, we propose the integration of hardware accelerators in the cloud as a way to maintain a positive performance trend. Field programmable gate arrays (FPGAs) represent the ideal way to integrate accelerators in the cloud, since they can be reprogrammed as needs change and allow multiple accelerators to share optimised communication infrastructure. We discuss a framework that integrates reconfigurable accelerators in a standard server with virtualised resource management and communication. We then present a case study that quantifies the efficiency benefits and break-even point for integrating FPGAs in the cloud
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