Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Parallel Processing

Parallel Processing

The brain processes sensory information rapidly due to parallel processing, which involves sending data across multiple neural pathways at the same time. This method allows the brain to manage various sensory qualities, such as shapes, colors, movements, and locations, all concurrently. For instance, when observing a forest landscape, the brain simultaneously processes the movement of leaves, the shapes of trees, the depth between them, and the various shades of green. This enables a quick and...

Acceleration Vectors

Acceleration Vectors

In everyday conversation, accelerating means speeding up. Acceleration is a vector in the same direction as the change in velocity, Δv, therefore the greater the acceleration, the greater the change in velocity over a given time. Since velocity is a vector, it can change in magnitude, direction, or both. Thus acceleration is a change in speed or direction, or both. For example, if a runner traveling at 10 km/h due east slows to a stop, reverses direction, and continues their run at 10 km/h...

Improving Translational Accuracy

Improving Translational Accuracy

Improving Translational Accuracy

Improving Translational Accuracy

Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...

Cross Product

Cross Product

The cross product is a fundamental concept in vector algebra that is a vector operation on two different vectors to obtain a third vector. Unlike the scalar product, the cross product results in a vector quantity perpendicular to both the original vectors.
The magnitude of the cross product is obtained by multiplying the magnitude of both the vectors and the sine of the angle between them. This means that a larger angle between the vectors will lead to a greater magnitude of the cross product.

Accelerating Fluids

Accelerating Fluids

When a fluid is in constant acceleration, the pressure and buoyant force equations are modified. Suppose a beaker is placed in an elevator accelerating upward with a constant acceleration, a. In the beaker, assume there is a thin cylinder of height h with an infinitesimal cross-sectional area, ΔS.
The motion of the liquid within this infinitesimal cylinder is considered to obtain the pressure difference. Three vertical forces act on this liquid:

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

MicroRNA-18a promotes hepatocellular carcinoma proliferation, migration, and invasion by targeting Bcl2L10.

OncoTargets and therapy·2018

Same author

Anatomical variation of infra-pyloric artery origination: A prospective multicenter observational study (IPA-Origin).

Chinese journal of cancer research = Chung-kuo yen cheng yen chiu·2018

Same author

Progression in Vascular Cognitive Impairment: Pathogenesis, Neuroimaging Evaluation, and Treatment.

Cell transplantation·2018

Same author

Risk factors analysis for hyperuricemic nephropathy among CKD stages 3-4 patients: an epidemiological study of hyperuricemia in CKD stages 3-4 patients in Ningbo, China.

Renal failure·2018

Same author

Asymptotic analysis of V-BLAST MIMO for coherent optical wireless communications in Gamma-Gamma turbulence.

Optics express·2018

Same author

Model-Based and Model-Free Techniques for Amyotrophic Lateral Sclerosis Diagnostic Prediction and Patient Clustering.

Neuroinformatics·2018

Search research articles

Related Experiment Video

Updated: Dec 8, 2025

Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders

Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders

Published on: November 1, 2024

Accelerating Spatial Cross-Matching on CPU-GPU Hybrid Platform With CUDA and OpenACC.

Furqan Baig¹, Chao Gao², Dejun Teng¹

¹Computer Science Department, Stony Brook University, Stony Brook, NY, United States.

Frontiers in Big Data

|September 21, 2020

Summary

This study introduces a CPU-GPU hybrid platform for accelerating geospatial cross-matching operations. The findings show that while CUDA offers superior performance, OpenACC provides a balance of portability and significant speedups over CPU-only methods.

Keywords:

cpugpu-hybrid geospatial gpgpu gpu openacc spatial-cross-matching spatial-join

More Related Videos

Design and Optimization Strategies of a High-Performance Vented Box

Design and Optimization Strategies of a High-Performance Vented Box

Published on: June 9, 2023

Operation of the Collaborative Composite Manufacturing CCM System

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

Related Experiment Videos

Last Updated: Dec 8, 2025

Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders

Author Spotlight: Deciphering Electrical Networks Behind Complex Brain Activities and Disorders

Published on: November 1, 2024

Design and Optimization Strategies of a High-Performance Vented Box

Design and Optimization Strategies of a High-Performance Vented Box

Published on: June 9, 2023

Operation of the Collaborative Composite Manufacturing CCM System

Operation of the Collaborative Composite Manufacturing CCM System

Published on: October 1, 2019

Area of Science:

Geographic Information Systems (GIS)
High-Performance Computing (HPC)
Computational Geometry

Background:

Spatial cross-matching of geospatial polygonal datasets is computationally demanding.
Modern systems with multiple processing units (CPUs and GPUs) offer opportunities for parallelization.

Purpose of the Study:

To develop and evaluate a CPU-GPU hybrid platform for accelerating geospatial dataset cross-matching.
To compare the performance and portability of CUDA and OpenACC implementations for GPU-accelerated cross-matching.

Main Methods:

A dynamic scheduling pipeline for geospatial subtasks on CPU or GPU.
Pixelization approach for GPU processing, converting floating-point vertices to integers using adaptive scaling.
Comparative analysis of CUDA and OpenACC accelerated C++ implementations.

Main Results:

CUDA implementations yield higher performance, while OpenACC offers better portability and extensibility with substantial CPU performance gains.
Larger datasets mitigate the Input/Output (IO) overhead associated with GPU computations.
Cost-effective GPU acceleration is demonstrated for efficient cross-matching.

Conclusions:

CPU-GPU hybrid platforms effectively accelerate geospatial cross-matching.
OpenACC presents a viable, portable alternative to CUDA for GPU acceleration in geospatial applications.
Optimizing resource utilization is key for efficient processing of large geospatial datasets.