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1 Java application that runs on standard CPUs (Central Processing Units).
2  on test sets is close to the result using a central processing unit.
3  the time required for this computation on a central processing unit.
4 ic detail only required about one hour on 48 Central Processing Units.
5 tecture for a classical computer comprises a central processing unit and a memory holding instruction
6                    By employing tens of fast central processing units and an advanced phase-space sam
7 compared with other methods, requires modest central processing unit consumption, and is robust with
8 e rise of multi-core processors, both in the central processing unit (CPU) and Graphics processing un
9 anual or semi-manual techniques with desktop central processing unit (CPU) runtimes faster than acqui
10 ts packing interactions function as a simple central processing unit (CPU) that senses multiple input
11 uilibration is almost three times as fast in central processing unit (CPU) time compared with a purel
12 an dynamics gives a sevenfold improvement in central processing unit (CPU) time with the choice of a
13 oftware that controls the temperature of the central processing unit (CPU), allowing for highly effic
14 he sequential implementation of the NRM on a central processing unit (CPU).
15 nsors on the same chip to create "biological central processing units (CPUs)" with multiple BSC eleme
16                         Mitochondria are the central processing units for cellular energy metabolism
17 field simulations and a total of 0.8 million central processing unit hours.
18 e histidine autokinase CheA functions as the central processing unit in the Escherichia coli chemotax
19 alled, and refrigerators or freezers and the central-processing unit of each computer were placed out
20                     We demonstrate a quantum central processing unit that exchanges data with a quant
21 ves a superior performance on memory use and central processing unit time than most current assembler
22 ality and requires lower memory use and less central processing unit time, especially for large genom
23 tructed a parallel computer cluster with 256 central processing units to analyse molecular data on a
24 ing substantial speedup over the traditional central processing unit version.

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