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  1. 1341
    “…This engine is implemented for both CPU and GPU. Firstly, this paper shows how such an engine speeds up the optimization process, even for small problems. …”
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    A Differentiable Physics Engine for Deep Learning in Robotics
  2. 1342
    “…Furthermore, we built a dual-core CPU combining two orthogonal core processors in a single cell. …”
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    A CRISPR/Cas9-based central processing unit to program complex logic computation in human cells
  3. 1343
    “…Depending on the configuration, distributing data in a larger number of cores allows reaching speedups of up to 121 over the CPU implementation. Moreover, we show that SEMs can be estimated with big data sets using current state-of-the-art algorithms for multi-block data analysis.…”
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    Big data in multi-block data analysis: An approach to parallelizing Partial Least Squares Mode B algorithm
  4. 1344
    “…Crisflash is over an order of magnitude faster than comparable tools, even using a single CPU core, and efficiently and robustly scores the potential off-targeting of all possible candidate CRISPR guide oligonucleotides. …”
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    Crisflash: open-source software to generate CRISPR guide RNAs against genomes annotated with individual variation
  5. 1345
    “…Computational requirements for a typical sample vary between 0.7 and 14 CPU hours per sample. AVAILABILITY AND IMPLEMENTATION: HLA*LA is implemented in C++ and Perl and freely available as a bioconda package or from https://github.com/DiltheyLab/HLA-LA (GPL v3). …”
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    HLA*LA—HLA typing from linearly projected graph alignments
  6. 1346
    por Franke, Karl R., Crowgey, Erin L.
    Publicado 2020
    “…Additionally, the IBM POWER9 CPU performed well on bioinformatic workloads when tested with 10 different tools for alignment/mapping.…”
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    Accelerating next generation sequencing data analysis: an evaluation of optimized best practices for Genome Analysis Toolkit algorithms
  7. 1347
    “…Our GPU implementation shows a 6.5x speedup with respect to the original version running on AMD dual-core CPU for the same problem size.…”
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    Accelerating Dock6’s Amber Scoring with Graphic Processing Unit
  8. 1348
    por Singh, Harendra
    Publicado 2020
    “…Efficiency of proposed method is shown by listing CPU time. Proposed computational method will work for long time domain. …”
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    Analysis for fractional dynamics of Ebola virus model
  9. 1349
    “…Our results show an average speedup of 14 (with a maximum of over 200) for 5262 reconstructed neutrino events of different flavors on a Titan V GPU compared to the multithreaded CPU version, which enables quicker and broader analysis of IceCube events.…”
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    Reconstruction of Low Energy Neutrino Events with GPUs at IceCube
  10. 1350
    “…A regression machine learning algorithm was chosen so as to require the smallest amount of resources (memory, CPU) and be able to run in a microcontroller. The algorithm has been designed and coded following specific conditions and specifications. …”
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    PortWeather: A Lightweight Onboard Solution for Real-Time Weather Prediction
  11. 1351
    “…HPC monitoring tasks generate a huge number of key performance indicators (KPIs) to supervise the status of the jobs running in these systems. KPIs give data about CPU usage, memory usage, network (interface) traffic, or other sensors that monitor the hardware. …”
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    Unsupervised KPIs-Based Clustering of Jobs in HPC Data Centers
  12. 1352
    “…In most cases, the results found using an open-source MILP solver suggest that high quality solutions can be achieved within an acceptable CPU time. We also project that our findings can be of general interest for other personnel scheduling problems, especially during emergency scenarios such as those related to Covid-19 pandemic.…”
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    Personnel scheduling during Covid-19 pandemic
  13. 1353
    “…We solve the partial differential equations on a GPU, demonstrating a speedup of ∼100 over the same resolution on a 20 cores CPU.…”
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    Accelerating the Finite-Element Method for Reaction-Diffusion Simulations on GPUs with CUDA
  14. 1354
    “…Efficiency of the proposed method is shown by listing the CPU time. It is shown that this method will work also for long-time behaviour. …”
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    Numerical simulation and stability analysis for the fractional-order dynamics of COVID-19
  15. 1355
    “…Experiments on OTB-2015, Temple Color 128 and UAV123 (including UAV20L) demonstrate that our tracker performs favorably against state-of-the-art trackers with light computation and runs over 100 fps on desktop computer with Intel i7-8700 CPU(3.2 GHz).…”
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    Efficient and Practical Correlation Filter Tracking
  16. 1356
    “…We also show a comparison of the performance on CPU and GPU implementations, demonstrating the power of algorithmic parallelization in the coming era of heterogeneous computing in high-energy physics.…”
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    CLUE: A Fast Parallel Clustering Algorithm for High Granularity Calorimeters in High-Energy Physics
  17. 1357
    “…A novel optimization problem is formulated to minimize the total system energy consumption under the constraints of data transmission rate and transmitting power requirements by jointly considering power allocation, CPU frequency, offloading weight factor and energy harvest weight factor. …”
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    Energy Efficient SWIPT Based Mobile Edge Computing Framework for WSN-Assisted IoT
  18. 1358
    “…The inference time was also evaluated, for these models, on CPU and GPU. The results showed that YOLOv4 Tiny was the fastest detector running on GPU (8 ms). …”
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    Visible and Thermal Image-Based Trunk Detection with Deep Learning for Forestry Mobile Robotics
  19. 1359
    “…The evaluation parameters include the signal-to-noise ratio and normalized mean absolute error of the PAI image and the CPU time. The comparative results demonstrate that the TVAL3 algorithm can well balance the quality and efficiency of the reconstruction. …”
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    A Comparative Study of Four Total Variational Regularization Reconstruction Algorithms for Sparse-View Photoacoustic Imaging
  20. 1360
    “…The proposed algorithm is executed on CPU as well as GPU and calculated the acceleration ratio of the model. …”
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    Feature-Based Sentimental Analysis on Public Attention towards COVID-19 Using CUDA-SADBM Classification Model
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