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In recent years, GPU CPU heterogeneous architectures have been increasingly adopted in high performance computing, because of their capabilities of providing high computational throughput.
The general-purpose computing on graphic processing units (GPGPUs) becomes increasingly popular due to its high computational throughput for data parallel applications.
Another challenge with STAP processing is that it requires a very high computational throughput.
The computational throughput requirement could be as high as 2 to 10 trillion operations per second, which is too high for conventional parallel processors.
This methodology utilizes the very high computational throughput capabilities of a GPU to accelerate ion trajectory modeling by ∼10,000 fold over simple CPU based systems.
Conventional multicore architectures can achieve a limited computational throughput due to the inherent multi-hop nature of the on-chip network infrastructure.
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However, the traditional method of raising core frequency to gain more speed--and thus computational throughput--has recently become limited due to high thermal dissipation, and the fact that semiconductor manufacturers are attacking atomic barriers in transistor design.
Multiple techniques of link adaptation were employed to develop a low computational complexity, throughput enhancing model.
Using a four-stage computational high throughput screening (HTS) of three National Cancer Institute compound libraries, P02 was identified as a potential β-OG pocket binder.
Greeley, J., Jaramillo, T. F., Bonde, J., Chorkendorff, I. & Nørskov, J. K. Computational high-throughput screening of electrocatalytic materials for hydrogen evolution.
However, no experimental or computational high-throughput method for target site identification in animals has been published yet.
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