“…However there is always performance penalty with virtualization, especially for short jobs which are always the case for volunteer computing tasks, the overhead of virtualization becomes a big portion in the wall time, hence it leads to low CPU efficiency of the jobs. With the wide usage of containers in HEP computing, we explore the possibility of adopting the container technology into the ATLAS BOINC project, hence we implemented a Native version in BOINC, which uses the singularity container or direct usage of the target OS to replace VirtualBox. …”
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“…Given that the increase of CPU performance has slowed down in recent years, the predicted performance of the software trigger currently falls short of the necessary 30MHz throughput. …”
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“…Modeling the physics of the detector response to particle collisions is one of the most CPU intensive and time consuming aspects of LHC computing. …”
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“…However there is always performance penalty with virtualization, especially for short jobs which are always the case for volunteer computing tasks, the overhead of virtualization becomes a big portion in the wall time, hence it leads to low CPU efficiency of the jobs. With the wide usage of containers in HEP computing, we explore the possibility of adopting the container technology into the ATLAS BOINC project, hence we implemented a Native version in BOINC, which uses the singularity container or direct usage of the target OS to replace VirtualBox. …”
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“…In this session we will try to make use of the integrated GPU that is part of most of the modern Intel CPUs, and demonstrate how, even on a laptop, you can run programs in a <em>heterogeneous</em> (CPU + GPU) way.</span></span></span></span></p> <p><span><span><span><span style="color:black">Ahmad Hesam is a Fellow in the CERN openlab IT section working on a simulation platform for biomedical models. …”
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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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“…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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“…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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“…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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“…Training of the neural network models, defined using the Keras API, is performed in a distributed fashion on Spark clusters by using BigDL with Analytics Zoo and also by using TensorFlow, notably for distributed training on CPU and using GPUs. The implementation and the results of the distributed training are described in detail in this work.…”
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“…Modeling the physics of a detector's response to particle collisions is one of the most CPU intensive and time consuming aspects of LHC computing. …”
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“…However, this accuracy comes with a high price in CPU, and the sensitivity of many physics analyses is already limited by the available Monte Carlo statistics and will be even more so in the future. …”
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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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“…Starting from the next LHC run, the upgraded LHCb data acquisition system will read and process events at the full LHC collision rate (averaging 30 MHz) by means of a large CPU farm. In order to save the power and flexibility of CPUs for the higher level tasks, an effort is being made to address the lowest-level, more repetitive tasks at the earliest stages of the data acquisition, by means of specialized processors, generally called “accelerators”. …”
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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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“…The CORSIKA 8 project aims to obtain high performance by exploiting techniques such as vectorization, gpu/cpu parallelization, extended use of static polymorphism and the most precise physical models available. …”
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“…Therefore it can run in the LHCb FPGA readout cards in real time, during data taking at 30 MHz, representing a promising alternative solution to more common CPU-based algorithms.…”
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“…Our model takes only a fraction of the time necessary for conventional detector simulation methods, running on a CPU in less than a millisecond per event.…”
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“…We find a considerable speedup over CPU-based execution is possible, potentially enabling such algorithms to be used effectively in future computing workflows and the FPGA-based Level-1 trigger at the CERN Large Hadron Collider.…”
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“…An exploratory effort was undertaken to create a hardware decoder for Field Programmable Gate Arrays (FPGA) to cut down on CPU usage from software decoders later in the system. …”
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