“…We benchmarked our system by screening 50 million HAC 22 molecules against the DRD4 receptor with an average CPU time of around 1 s per molecule. We saw up to 3-fold variations in cost between AWS availability zones. …”
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“…In this study, we integrated gene expression, DNA methylation, and genome variants from the iMETHYL database using the recently proposed kernel tensor decomposition-based unsupervised feature extraction method with limited computational resources (i.e., short CPU time and small memory requirements). Our methods do not require prior knowledge of the subjects because they are fully unsupervised in that unsupervised tensor decomposition is used. …”
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“…The effectiveness of this approach has been proved through experiments comparing silhouette coefficient and CPU time.…”
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“…We extensively evaluated these models with various intrinsic parameters and compared their performance with conventional CPU-based implementations. While being neural approximations, we show that neuromorphic models can perform competitively with their conventional counterparts. …”
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“…Standard 3D convolutions impose much higher CPU and memory requirements than do the same 2D operations. …”
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“…While each cryptographic method completes the same objective, they all employ different amounts of CPU, memory, throughput, encryption, and decryption times. …”
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“…Numerous numerical simulations validate the performance of two matrix collocation schemes and demonstrate the accuracy as well as the gain in computational efficiency in terms of elapsed CPU time. The proposed matrix algorithms for computation are easy to implement and straightforward, and provide more accuracy compared to other available computational values in the literature.…”
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“…When running on a 2 Ghz Intel CPU, the task of 3D median filtering on a typical 256 megabyte dataset takes two and a half hours, whereas by using 1024 nodes of Blue Gene, this task can be performed in 18.8 seconds, a 478× speedup. …”
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“…Our scheme maintains the original precision and involves no data exchange between the GPU and CPU. The merits of our scheme are demonstrated in numerical experiments against the traditional implementation. …”
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“…Our results indicate that the GPU implementation can maintain original precision and speed up the reconstruction process by 110–120 times for circular cone-beam scan, as compared to traditional CPU implementation.…”
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“…A total of 21 428 residues in these maps were traced in 24 CPU min with an overall r.m.s.d. of 1.61 Å for C(α) atoms compared with the known refined structures. …”
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“…Real-time processing and displaying of the structure and blood vessel images are very interesting and is demonstrated using a dual quad-core Central Processing Unit (CPU) workstation. High resolution images of choroidal capillary of the vasculature network with phased-resolved color Doppler and Doppler variance are shown.…”
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“…Simulations with more than one million particles on a single GPU card exhibit speedups of up to two orders of magnitude over using a single-core CPU. It is demonstrated that the code achieves different speedups with different CUDA-enabled GPUs. …”
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“…The effects of double and single precision integration are discussed, and mixed precision GPU integration is shown to give extremely good numerical accuracy for both CIS and TDDFT excitation energies (excitation energies within 0.0005 eV of extended double precision CPU results).…”
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“…The result is that the GPU can complete the denoising in about 25 minutes if spatial filtering is used and in about 8 minutes if FFT-based filtering is used. The CPU implementation requires several days of processing time for spatial filtering and about 50 minutes for FFT-based filtering. …”
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“…The average processing rate for these images was 8 Mpx/s/cpu (2.6 GHz Intel Core2, 2 GB RAM). This translates to 35 processed frames per second for a 640 px×352 px video of 4 whiskers. …”
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“…The OSEM reconstruction algorithms were implemented employing both CPU-based and GPU-based codes, and their computational performance was quantitatively analyzed and compared. …”
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“…This paper involves both the laboratory based E/M impedance method development, its implementation into a CPU with limited resources as well as a comparison with experimental testing data needed to demonstrate the feasibility of flaw detection on composite materials and answer the question of the method reliability. …”
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“…One of the most accurate multi-class protein classification systems continues to be the profile-based SVM kernel introduced by the Leslie group. Unfortunately, its CPU requirements render it too slow for practical applications of large-scale classification tasks. …”
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“…The system is composed of a CPU, microwave module, temperature sensor, pressure sensor and humidity sensor array. …”
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