ライフサイエンスコーパス: CPU

1 results, the protocol requires roughly 1,000 CPU-hours for antibody modeling and 250 CPU-hours for an

2 ase Control Consortium, RAPID ran in about 1 CPU-hour per dataset, and identified many significant in

3 round half an hour on a small server with 10 CPUs to access genotypes of approximately 60 million var

4 entire fish genomes (470 and 217 Mb) in 120 CPU hours using 15 processors on a single machine.

5 sks achieving a reduction up to 30% for a 15 CPUs machine.

6 STX) range mostly from 4 to 10 (resp. With 2 CPU threads and 2 GPUs, H-BLAST can be faster than 16-th

7 lPhiPKa and can run a single job on up to 24 CPUs.

8 igh computational demands (currently ~30-250 CPU hours per sample) remain a significant challenge to

9 ,000 CPU-hours for antibody modeling and 250 CPU-hours for antibody-antigen docking.

10 ring of all 54,118 NCBI RefSeq genomes in 33 CPU h; real-time database search using assembled or unas

11 lly reduce wallclock time from 27 days on 40 CPUs to a single day using 4104 tasks, each task utilizi

12 ty to create computing clusters with 16-480+ CPUs.

13 ical alignments take only a median time of 5 CPU seconds in a single R12000 processor.

14 g arrays to the entire genome in less than 6 CPU hours.

15 A CPU located in the emergency department can be a safe, e

16 modeling that relies on MODELLER; MOULDER, a CPU intensive protocol of MODWEB for building comparativ

17 -fold speedup compared to a single core of a CPU can be achieved for a network of one million conduct

18 safety, efficacy, and cost of admission to a CPU as compared with those of regular hospital admission

19 ts with no ischemic ECG changes triaged to a CPU were randomized to CA (n = 123) or ETT (n = 125).

20 es order-of-magnitude speedups relative to a CPU-based ordinary differential equation integrator.

21 vector extension intrinsics code accelerate CPU calculations, and OpenCL kernels support AMD and Nvi

22 add-on required relatively little additional CPU time.

23 fering state of the art ratios at affordable CPU costs.

24 Analogous CPU elements may be found in other receptors and signali

25 d does not demand a lot of system memory and CPU resources.

26 entials between GPU assisted performance and CPU executions as the computational load increases for h

27 TK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and

28 es in hardware architecture between GPUs and CPUs complicate the porting of existing code.

29 actor IX-deficient plasma with specific anti-CPU antibodies prevents the increased resistance to fibr

30 lecular dynamics (MD) simulations, which are CPU-demanding and not yet particularly accurate.

31 icity in the detection of splices as well as CPU and memory efficiency.

32 including Python, Matlab and Java as well as CPU versus GPU implementations.

33 extensions are limited only by the available CPU.

34 ssue types, but existing approaches are both CPU and memory-intensive, limiting their application to

35 rithm is asymptotically optimal O(N) in both CPU time and required memory, and application to the ace

36 all supported hardware types (including both CPUs and GPUs) and perform well on all of them.

37 Rats with hippocampus, medial caudoputamen (CPU), lateral CPU, or control lesions were trained on de

38 bootstrap resampling and only costs computer CPU time.

39 In our experiments with a four core CPU and GPU, SWIFTLINK achieves a 8.5x speed-up over the

40 was commissioned in 2010, yet its eight-core CPUs with only 24GB RAM work well in 2017 for these dual

41 timized for performance on modern multi-core CPUs with SSE capabilities, only a few acceleration atte

42 ol for a heterogeneous computer that couples CPUs and GPUs, to accelerate BLASTX and BLASTP-basic too

43 sequence identity was accomplished in 2 days CPU time, and the removal of fragments and close similar

44 mation is derived which allows for efficient CPU processing times.

45 using 4104 tasks, each task utilizing eight CPUs and taking less than 7 minutes to complete.

46 , comprehensive evaluations against high-end CPUs (Intel i5, i7 and Xeon) shows that CUDAMPF yields u

47 s and epistasis networks, and for estimating CPU time and disk space requirements.

48 s in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimi

49 or parallel execution of tasks, uses C++ for CPU and I/O intensive calculations, and stores intermedi

50 dividual small tasks tempers competition for CPU time in the shared HPC environment, and jobs submitt

51 s 3D models of proteins without the need for CPU intensive structural alignments by utilizing the Q m

52 s takes only a couple of hours (on a 1.2 GHz CPU, 1 GB RAM machine) to run on a dataset 28 Mb of barl

53 ed implementation utilizing multicore hybrid CPU/GPU computing resources, which can process terabytes

54 h, however, requires very little increase in CPU time.

55 oximately equal to the number of independent CPUs operating on the data.

56 RMSD calculations using a laptop CPU are 60x faster than qcprot and 3x faster than curren

57 pocampus, medial caudoputamen (CPU), lateral CPU, or control lesions were trained on declarative and

58 Rats with lateral CPU lesions were not impaired on either version of the t

59 Allele elimination requires less CPU time and memory, but does not always eliminate all i

60 eins in the size range of 10-25 kDa the less CPU intensive restrained Rosetta refinement protocols pr

61 microenvironmental effects takes very little CPU time, the computational speed of the SCP formulation

62 Benchmarking indicates that SeqLib has lower CPU and memory requirements than leading C ++ sequence a

63 , but may require considerable time and many CPUs.

64 Medial CPU lesions impaired rats' ability to learn the procedur

65 est a double dissociation between the medial CPU and hippocampus in processing egocentric-procedural

66 Median CPU time for ortholog prediction per gene by OrthoReD ex

67 We analyse the memory, CPU, I/O usage and file sizes used by Gap5.

68 t networks of several thousand genes in mere CPU seconds on a desktop workstation.

69 stributed on a grid of more than 1.5 million CPUs worldwide (World Community Grid).

70 ies, while a low-memory footprint and modest CPU requirements allow it to operate on a personal compu

71 memory per computational thread and 15x more CPU time than Beagle.

72 sometimes better, than popular and much more CPU-intensive methods for discrimination, including lass

73 ull MD simulations require 200 times as much CPU time as the implicit water LD simulations.

74 The system can run on multi-CPU architectures including SMP and PVM.

75 the compute capabilities of common multicore CPU clusters.

76 ltiview image fusion optimized for multicore CPU architectures, reducing image data size 30-500-fold;

77 On Intel Haswell multicore CPUs, for a single query, the single-threaded muBLASTP a

78 Unix-based desktops or servers with multiple CPUs.

79 mpute node with two multi-core Intel Nehalem CPUs, from approximately 17 h to approximately 11 min.

80 pression rates, or require a great amount of CPU time for decompression and loading every time the da

81 onal challenge for search, requiring days of CPU time to annotate an organism's proteome.

82 ulin, presumably by increasing the degree of CPU activation produced by the low levels of thrombin ge

83 e on-pathway intermediate, and the demand of CPU power is moderate.

84 ese additions enhance the rate and extent of CPU activation: in the case of factor IX, presumably by

85 ng with Langevin dynamics required 2-10 h of CPU time on average with a single AMD Athlon MP 2800+ pr

86 average, this requires approximately 29 h of CPU time per sequence.

87 two weeks, a day and a half, and an hour of CPU time, respectively.

88 overall memory usage but also the number of CPU operations per alignment.

89 If we solved the problem of CPU-time required to apply AGAPE on millions of proteins

90 ightning-fast, consuming only few seconds of CPU time to generate fragment library for a protein of t

91 f the Markov Chain is short both in terms of CPU times and number of proposals.

92 ed suffix arrays, EMSAR minimizes the use of CPU time and memory while achieving accuracy comparable

93 ets with 30 taxa or more after many weeks of CPU runtime.

94 firm that REST greatly reduces the number of CPUs required by regular replica exchange and increases

95 ng 3D model quality; however, they are often CPU intensive as they carry out multiple structural alig

96 This leads to increasing strain on CPU resources and decreasing density of first-hand annot

97 Retention of ECs seeded onto CPU precoated with SMCs was significantly improved by a

98 ear 90-fold speed increase over an optimized CPU-based computation and a >140-fold increase over the

99 ATI 5870 GPU, on average, than the original CPU single-threaded implementation on an AMD Phenom II 8

100 ning highly parallel programs and outperform CPUs in terms of raw computing power.

101 and decodes up to 420 million genotypes per CPU second.

102 d processes 30 million name-strings/hour per CPU thread.

103 ystems, mapping nearly 2.2 million reads per CPU hour, which is sufficient to process an entire RNA-S

104 riventricular nucleus (Pe), caudate putamen (CPU) and the ependymal lining of the ventricles.

105 n was first detected in the caudate-putamen (CPU) at e12.5, and by e15.5, activity had not only incre

106 ib structure of some populations and reduces CPU time.

107 meters were optimized to reduce the required CPU time to approximately 17 min, while retaining TASSER

108 orders of magnitude speed-up over respective CPU-based clustering algorithms and is intended as an op

109 s a ~40X speedup when compared with BEAGLE's CPU implementation on a dual Xeon 5520 and 3X speedup ve

110 undreds of hours of running time on a single CPU even for the fastest known implementations.

111 Using a single CPU Roary can produce a pan genome consisting of 1000 is

112 I finds influencers in 2.5 hours on a single CPU, while all BP algorithms (CIP, CIBP and BDP) would t

113 s using less than 239 MB of RAM and a single CPU.

114 sequences at a rate of 3.5 Mb/s on a single CPU.

115 runtime is attained when compared to single CPU implementations.

116 MoTeX-II comes in three flavors: a standard CPU version; an OpenMP-based version; and an MPI-based v

117 a dramatically lower cost than the standard CPU-based implementations.

118 pular Java application that runs on standard CPUs (Central Processing Units).

119 istakes executes interactively on the system CPU while the GPU handles 3-D visualization tasks.

120 The CPU was managed by the emergency department staff.

121 s between the two groups (odds ratio for the CPU group as compared with the hospital-admission group,

122 However, the CPU-intensive nature of document comparison has limited

123 edial habenula, and medulla and at p1 in the CPU at levels noticeably less than those of the MOR.

124 heart failure), and the 212 patients in the CPU group had 7 events (5 myocardial infarctions, 1 deat

125 In low-risk patients in the CPU, a strategy of CA detects more CAD than ETT, reduces

126 rownian simulation, but at a fraction of the CPU time (10(-4) to 10(-3), depending on the model).

127 usands of conditions in a few minutes of the CPU time on a desktop computer.

128 -Skim uses <4% of the k-mers and <10% of the CPU time required by Sailfish.

129 ized and parallelized across 16 cores on the CPU.

130 ethod allowed us to significantly reduce the CPU time required to cluster these large compound librar

131 y, this method has significantly reduced the CPU time for modelling.

132 This method reduces the CPU time required for calculating thermodynamic averages

133 l admission than among those assigned to the CPU (P<0.01 by the rank-sum test).

134 the cardiology service) or admission to the CPU (where patients were cared for according to a strict

135 ong the 97 patients who were assigned to the CPU and discharged.

136 ever, with comparable effort, multi-threaded CPU implementations negate the apparent advantage of GPU

137 When compared with naive, single-threaded CPU implementations, the GPU yields a large improvement

138 iated in part by plasma carboxypeptidase-U ([CPU] carboxypeptidase-R, procarboxypeptidase-B, thrombin

139 admission to a chest-pain observation unit (CPU) located in the emergency department for such patien

140 in low-risk patients in the chest pain unit (CPU) to reduce repeat emergency department (ED) visits a

141 essors, both in the central processing unit (CPU) and Graphics processing unit processor markets, ena

142 niques with desktop central processing unit (CPU) runtimes faster than acquisition time for up to hun

143 unction as a simple central processing unit (CPU) that senses multiple input signals, integrates thes

144 ee times as fast in central processing unit (CPU) time compared with a purely molecular dynamics (MD)

145 fold improvement in central processing unit (CPU) time with the choice of a simple centripetal biasin

146 temperature of the central processing unit (CPU), allowing for highly efficient PCR.

147 ion of the NRM on a central processing unit (CPU).

148 create "biological central processing units (CPUs)" with multiple BSC elements, capable of processing

149 d of compliant poly(carbonate-urea)urethane (CPU), incorporated with human smooth muscle cells (SMCs)

150 s defined as 'chronic persistent urticaria' (CPU), while the presence of urticaria for 2-4 days a wee

151 echanism for better efficiency among various CPUs and GPUs combinations.

152 ion power donated from over 20,000 volunteer CPUs, FALCON@home shows a throughput as high as processi

153 n revealed that 14 of 58 patients (24%) with CPU and one of 10 patients with CRU (10%) were aspirin h

154 nts with CRU compared with the patients with CPU (P < 0.016, P = 0.024, respectively).

155 In a modern machine (2 Intel Xeon X5650 CPUs, 48 GB memory), when fast turn-around is needed, Se

156 implementations have been developed for x86 CPUs, most are embedded into larger database search tool