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1725por Corona Rodríguez, Mtro. José ManuelEnlace del recurso
Publicado 2014
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Online Artículo -
1726por Sadasivan, Harisankar, Maric, Milos, Dawson, Eric, Iyer, Vishanth, Israeli, Johnny, Narayanasamy, Satish“…. ~60-70% of the run-time on a CPU comes from the highly sequential chaining step in Minimap2. …”
Publicado 2023
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1727por Cetin-Karayumak, Suheyla, Zhang, Fan, Billah, Tashrif, Zekelman, Leo, Makris, Nikos, Pieper, Steve, O’Donnell, Lauren J., Rathi, Yogesh“…This resource required significant computational effort, taking ~50,000 CPU hours to harmonize the data, perform white matter parcellation, and run whole brain tractography. …”
Publicado 2023
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1728por Marriott, Heather, Kabiljo, Renata, Al Khleifat, Ahmad, Dobson, Richard J, Al-Chalabi, Ammar, Iacoangeli, Alfredo“…We developed DNAscan2, a highly flexible, end-to-end pipeline for the analysis of NGS data, which (i) can be used for the detection of multiple variant types, including SNVs, small indels, transposable elements, short tandem repeats, and other large structural variants; (ii) covers all standard steps of NGS analysis, from quality control of raw data and genome alignment to variant calling, annotation, and generation of reports for the interpretation and prioritization of results; (iii) is highly adaptable as it can be deployed and run via either a graphic user interface for non-bioinformaticians and a command line tool for personal computer usage; (iv) is scalable as it can be executed in parallel as a Snakemake workflow, and; (v) is computationally efficient by minimizing RAM and CPU time requirements. AVAILABILITY AND IMPLEMENTATION: DNAscan2 is implemented in Python3 and is available at https://github.com/KHP-Informatics/DNAscanv2.…”
Publicado 2023
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1729“…Compared to the sequential version executed on the CPU, the proposed parallel implementation was able to speed the execution time up to [Formula: see text] times.…”
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1730“…A comparison of GPU and CPU computations indicates a speed-up of the GPU performance of up to 100 times—depending on the number of disk objects.…”
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1731“…This artcle presents field-programmable gate array (FPGA) soft-core processors integration based on different instruction set architectures (ISA), custom central processing unit (CPU) datapath, dedicated hardware thread context, and hardware real-time operating system (RTOS) implementations. …”
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1732“…At the same time, the transmit power and CPU frequency of the UAV are adjusted to obtain the shortest time of an individual iteration round. …”
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1733“…Conclusions: Comprehensive experimental results demonstrate that the proposed end-to-end FPGA-based accelerated CNN achieves a negligible loss, a high speed for registration parameters, less power when compared to the CPU, and the potential for real-time medical imaging.…”
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1734por Zhong, Enmin, del-Blanco, Carlos R., Berjón, Daniel, Jaureguizar, Fernando, García, Narciso“…Notably, this approach achieves real-time performance using a standard CPU, distinguishing it from methods that require specialized GPUs. …”
Publicado 2023
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1735por Chaillet, Marten L., van der Schot, Gijs, Gubins, Ilja, Roet, Sander, Veltkamp, Remco C., Förster, Friedrich“…Sampling at the Crowther criterion, which was effectively impossible with CPU implementations due to the extensive computation times, allows for automated extraction with high sensitivity. …”
Publicado 2023
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1736“…Notably, our solution also exhibited a lower CPU and memory utilization, with an approximately 40% reduction compared to alternative scanners. …”
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1737por Klein, Michael T, Hou, Gang, Quann, Richard J, Wei, Wei, Liao, Kai H, Yang, Raymond S H, Campain, Julie A, Mazurek, Monica A, Broadbelt, Linda J“…BioMOL can build a detailed model in 1-1,000 CPU sec using standard desktop hardware. The models solve and optimize using standard and widely available hardware and software and can be presented in the context of a user-friendly interface. …”
Publicado 2002
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1738“…Furthermore, the consensus sequence add-on required relatively little additional CPU time. We discuss how advanced users of PSI-BLAST can immediately benefit from using consensus sequences on their local computers. …”
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1739“…The experimental results show a factor of 12.2 speedup over the RNAalifold (ViennaPackage – 1.6.5) software for a group of aligned RNA sequences with 2981-residue running on a Personal Computer (PC) platform with Pentium 4 2.6 GHz CPU.…”
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1740“…The proposed algorithm maintains a comparable CPU execution time with that of CD-HIT-EST which is much slower than UCLUST, and has successfully generated clusters with higher statistical accuracy than both CD-HIT-EST and UCLUST. …”
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