Sentence examples for cpu computational power from inspiring English sources

Exact(1)

However, such implementation can occupy all CPU computational power for this task alone; nevertheless, face/object detection is considered as prerequisite step for some of the main application such as biometric, content-base image retrieval systems, surveillance, and autonavigation.

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The conventional CPU-control GPU-compute pattern used in many appliCPU-control GPU-computeCPU-control GPU-computeer.

Amazon Web Services (AWS) of Amazon offers infrastructure as a service (IaaS) in terms of computational power (CPUs and RAM), storage, and connectivity.

Molpher leverages the computational power of modern CPUs by dividing chemical space exploration between individual CPU cores.

Quantum computers promise to bring computational power leaps and bounds ahead of our most advanced machines.

The amount of data available to researchers is growing exponentially while CPUs fall short on delivering the necessary computational power.

However, depending on the level of represented detail the steadily increasing computational power of modern processors (CPUs and GPUs) today permits the simulation of up to several millions of cells by agent-based models (Anderson et al., 2007; Drasdo et al., 2007 and refs. therein) provided an efficient implementation especially in three dimensions.

However, SW-CUDA distributed the SW algorithm among multicore CPUs and GPUs, making it a highly dependent CPU, owing to their inability to utilize the entire computational power of GPUs.

In this article, lattice Boltzmann simulations are performed on graphics processing units (GPUs), the computational power of which exceeds that of CPUs by more than one order of magnitude, to investigate incompressible Newtonian flow in idealized multi-scale particle fluid systems.

GPUs are massively parallel processors with more computational power and higher memory bandwidth than Central Processing Units (CPUs) (18)—the brain of the computer.

The network will initially start because computational power is cheap and early adopters are more inclined to devote CPUs to mining cycles than they are to dollars on a service they might not even want.

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