“…We will first talk about the Acceleration Stack for Intel Xeon CPU with FPGAs which makes it easy to create, verify, and execute functions on the Intel Programmable Acceleration Card in a Data Center. …”
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“…Some of them include: concise view of the most important DB metrics; top SQL statements based on CPU, executions, block reads, etc.; volume growth plots per schema and DB object type; database jobs section with signaling for problematic ones; in-depth analysis in case of contention on data or processes. …”
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“…Scalable multithreading poses challenges to I/O, and the performance of a thread-safe I/O strategy may depend upon many factors, including I/O latencies, whether tasks are CPU- or I/O-intensive, and thread count. In a multithreaded framework, an I/O infrastructure must efficiently supply event data to and collect it from many threads processing multiple events in flight. …”
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“…This can be done by simulating the workflows, using real metrics for task interdependencies and timing, as we vary fractions of offloaded tasks, latencies, data conversion speeds, memory bandwidths, and accelerator offloading parameters such as CPU/GPU ratios and speeds. We present the results of these studies, which will be instrumental in directing effort to make the ATLAS framework, kernels and workflows run efficiently on exascale facilities.…”
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“…One of the benefits we believe HammerCloud can provide is to be able to tune the commissioning of the new infrastructure, functional and also stress testing, as well as benchmarking with "standard candle" workflows, with experiment realistic workloads, that can be heavy for CPU, or I/O, or IOPS, or everything together. This extension of HammerCloud has been successfully used in CERN IT during the prototype phase of the "BEER" Batch on EOS (Evaluation of Resources) project, and is being integrated with the continuous integration/continuous deployment suite for Batch service VMs.…”
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“…The performance of a thread-safe I/O strategy may depend upon many factors, including I/O latencies, whether tasks are CPU- or I/O-intensive, and thread count. In a multithreaded framework, an I/O infrastructure must efficiently supply event data to and collect it from many threads processing multiple events in flight. …”
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“…Some of them include: A concise view of the most important DBmetrics; a list of top SQL statements based on CPU, executions, block reads, etc.; volume growth plots per schema and DB object type; a database jobs section with signalization for failures; and in-depth analysis in case of row-lock contention or DB sessions. …”
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“…Some of them include: concise view of the most important DB metrics; top SQL statements based on CPU, executions, block reads, etc.; volume growth plots per schema and DB object type; database jobs section with signaling for problematic ones; in-depth analysis in case of contention on data or processes.This presentation describes also the technical aspects of the implementation. …”
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“…A private Openstack Cloud has been deployed 2 years ago, and more and more internal customers are interested in using it, consequently increasing the cpu, memory and storage usages. So far, SAN storage was used for instances volumes, and scalability was complicated. …”
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“…It currently consists of the EOS system as storage back-end with a total gross capacity of 15.5 PB, and service nodes with a total of 2000 CPU cores. As main changes in 2019, the EOS service has been migrated to the QuarkDB namespace, and half of the service nodes have been migrated to FUSEX client. …”
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“…We discuss several aspects of the process of planning the trigger menu, including how rate, bandwidth, and CPU constraints are folded in during the compilation of the menu. …”
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“…We discuss several aspects of the process of planning the trigger menu, including how rate, bandwidth, and CPU constraints are folded in during the compilation of the menu. …”
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“…A special Geant4 Physics List configuration FTFP_BERT_EMM will be described, which provides a compromise between simulation accuracy and CPU performance. A significant fraction of time for simulation of CMS events is spent on tracking of charge particles in magnetic field. …”
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“…A solution of managing and scheduling heterogeneous computing resources (CPU and GPU) is proposed, which adopts Kubernetes to achieve centralized heterogeneous resources management and resource expansion on demand. …”
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“…We will show the improvement of CPU stability and data throughput reached.…”
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“…This work aims to implement such models onto an FPGA, which promises smaller latency with respect to traditional inference algorithms running on CPU, an important aspect for a trigger system. The analysis carried out in this work will use data obtained through Monte Carlo simulations of muons crossing the barrel region of the CMS muon chambers, and compare the results with the $p_T$ assigned by the current CMS Level 1 Barrel Muon Track Finder (BMTF) trigger system.…”
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“…--HTML--><p class="MsoPlainText"><strong><span><span>Lecture Contents</span></span></strong></p> <p class="MsoPlainText"><span><span>In this lecture, we will look into the basics of CPU hardware architecture and how it relates to performance. …”
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“…The landscape of computing power available for the CMS experiment is rapidly evolving, from a scenario dominated by x86 processors deployed at WLCG sites towards a more diverse mixture of Grid, HPC, and Cloud facilities, incorporating a higher fraction of non-CPU components such as GPUs. Using these facilities heterogeneous resources efficiently to process the vast amounts of data to be collected in the LHC Run3 and beyond, is key to CMS achieving its scientific goals. …”
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“…From dynamic load balancing in Kubernetes, to accelerated compression of tiles reducing both CPU and bandwidth use and improving interactivity. …”
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“…This report includes initial benchmarks of the batched computations strategy run on a CPU with vector instructions. Both strategies show significant performance improvements and the parallelization approach at its current state also proves to be robust enough to consistently fit state of the art physics models to real LHC data. …”
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