“…Since a tenfold increase in WLCG resources is not an option, a comprehensive model for the composition and execution of the data processing workflow within given CPU and storage constraints is necessary to accommodate physics needs of the next LHC run. …”
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“…The task requires using very large data sets and represents a considerable numerical challenge in terms of both CPU time and precision. The adopted strategy uses a hierarchical approach to alignment, combining local and global least squares techniques. …”
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“…The task requires using very large data sets and represents a considerable numerical challenge in terms of both CPU time and precision. The adopted strategy uses a hierarchical approach to alignment, combining local and global least squares techniques. …”
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“…The task requires using very large data sets and represents a considerable numerical challenge in terms of both CPU time and precision. The adopted strategy uses a hierarchical approach to alignment, combining local and global least squares techniques. …”
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“…Balanced Computing focuses on solving large computational problems requiring a roughly equivalent amount of CPU, memory and I/O. Time allowing, we will talk about Tetration Analytics, another “Big Data” use case using novel sensor technology. …”
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“…Focused on recent advances of modeling and optimization techniques aimed at handling computationally-expensive engineering problems involving simulation models, this book will be an invaluable resource for specialists (engineers, researchers, graduate students) working in areas as diverse as electrical engineering, mechanical and structural engineering, civil engineering, industrial engineering, hydrodynamics, aerospace engineering, microwave and antenna engineering, ocean science and climate modeling, and the automotive industry, where design processes are heavily based on CPU-heavy computer simulations. Various techniques, such as knowledge-based optimization, adjoint sensitivity techniques, and fast replacement models (to name just a few) are explored in-depth along with an array of the latest techniques to optimize the efficiency of the simulation-driven design process. …”
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“…In order to be able to make effective use of emerging hardware, where the amount of memory available to any CPU is rapidly decreasing as the core count continues to rise, ATLAS has begun a migration to a concurrent, multi-threaded software framework, known as AthenaMT. …”
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“…Written by a professional end-user of ASIC/SoC/CPU and FPGA design and Verification, this book explains each concept with easy to understand examples, simulation logs and applications derived from real projects. …”
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“…Performance metrics ranging from low level memory and CPU requirements, to shapes and efficiencies of high level physics quantities are visualized and validated by a range of experts. …”
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“…In order to be able to make effective use of emerging hardware, where the amount of memory available to any CPU is rapidly decreasing as the core count continues to rise, ATLAS has begun a migration to a concurrent, multi-threaded software framework, known as AthenaMT. …”
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“…CPU cycles for small experiments and projects can be scarce, thus making use of all available resources, whether dedicated or opportunistic, is mandatory. …”
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“…&nbsp;<br /> The challenge will run in two phases: &nbsp;the first on accuracy (no stringent limit on CPU time), starting in March 2018, and the second (starting in the summer 2018) on the throughput, for a similar accuracy.…”
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“…--HTML-->Fast calorimeter simulation in LHCb In HEP experiments CPU resources required by MC simulations are constantly growing and become a very large fraction of the total computing power (greater than 75%). …”
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“…Then we will focus on some scaling performance measurements executed with a cluster of 1000 CPU cores. In particular, we will: - Show the way Kubernetes scales in deploying containers as a function the cluster size; - Prove how a proper tuning of the Query Per Second (QPS) Kebernetes parameter set can improve the scaling of applications. …”
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“…To better match the increasing CPU core count and the, therefore, decreasing available memory per core, a multi-threaded framework, AthenaMT, has been designed and is now being implemented. …”
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“…I can over this talk recap the 9 years road I walked on with experience feedback showing sometimes impressive performance gaps on large real applications by considering the path from CPU caches, NUMA layout going through the OS paging system and malloc implementation closing by profiling real applications. …”
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“…Apache Spark has been used for the data lifting part of the pipeline, Spark with Analytics Zoo and BigDL have been used to run parallel training of the neural networks on CPU clusters.…”
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“…In this contribution, we present details on the integration of new components, such as HPC computing resources to execute ATLAS simulation workflows; the development of new techniques to improve efficiency in a cost-effective way, such as storage and CPU federations; and improvements in Data Organization, Management and Access through storage consolidations ("data-lakes"), the use of data Caches, and improving experiment data catalogues, like Event Index. …”
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“…The anticipated availability of an improved fast simulation will enable ATLAS to produce significantly larger Monte Carlo samples with the available CPU, which will then be limited by insufficient disk resources. …”
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“…Initial benchmarks show that the updated NetIO implementation yields the same or higher throughput, while the CPU resource utilization is reduced by an order of magnitude. …”
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