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Related Concept Videos

Parallel Processing01:20

Parallel Processing

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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...
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Multimachine Stability01:25

Multimachine Stability

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Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
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Non-ohmic Devices00:51

Non-ohmic Devices

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In most substances, the current flow is proportional to the voltage applied to it. A simple relationship between the values of current, voltage, and resistance is known as Ohm's law. Nonohmic devices do not exhibit a linear relationship between voltage and current. One such device is the semiconducting circuit element known as a diode. A diode is a circuit device that allows current flow in only one direction.
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Bus Impedance Matrix01:24

Bus Impedance Matrix

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Calculating subtransient fault currents for three-phase faults in an N-bus power system involves using the positive-sequence network. When a three-phase short circuit occurs at a specific bus, the analysis uses the superposition method to evaluate two separate circuits.
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Leaky Scanning02:28

Leaky Scanning

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During most eukaryotic translation processes, the small 40S ribosome subunit scans an mRNA from its 5' end until it encounters the first start AUG codon. The large 60S ribosomal subunit then joins the smaller one to initiate protein synthesis. The location of the translation initiation is largely determined by the nucleotides near the start codon as there may be multiple translation initiation sites present on the mRNA.  Marilyn Kozak discovered that the sequence RCCAUGG (where R...
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Clamper Circuit01:14

Clamper Circuit

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A clamper circuit, also known as a DC restorer, represents a specialized variant of the rectifier circuit, notable for its method of taking the output across the diode rather than the capacitor. This configuration lends to several distinctive applications, particularly in handling square wave inputs.
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CORAL: Verification-Aware OpenCL Based Read Mapper for Heterogeneous Systems.

Sidharth Maheshwari, Venkateshwarlu Y Gudur, Rishad Shafik

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    |September 29, 2019
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    Summary
    This summary is machine-generated.

    Genomics big data presents computational challenges. CORAL, a cross-platform read mapper, addresses these by utilizing heterogeneous computing resources like CPUs and GPUs for faster whole genome sequencing analysis.

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    Area of Science:

    • Genomics
    • Bioinformatics
    • Computational Biology

    Background:

    • Genomics aims to revolutionize medicine into a personalized, predictive, preventive, and participatory (P4) model.
    • The rapid growth of genomic data production presents significant computational challenges, particularly in whole genome sequencing (WGS) pipelines.
    • Existing read mapping tools struggle to efficiently utilize heterogeneous computing systems (CPUs, GPUs, FPGAs).

    Purpose of the Study:

    • To develop a read mapper that can execute on heterogeneous computing platforms simultaneously.
    • To reduce the computational cost and time associated with the read mapping step in WGS.
    • To improve filtration techniques for reducing verification overhead in read mapping.

    Main Methods:

    • Proposed CORAL (Cross-platfOrm Read mApper using opencL), a read mapper designed for heterogeneous environments.
    • Implemented workload distribution across multiple computing devices (CPUs and GPUs) without requiring platform-specific programming.
    • Integrated dynamic k-mer length adaptation during filtration to minimize verification costs.

    Main Results:

    • Achieved up to a 2x speedup by judiciously distributing workload across a quadcore Intel CPU and two Nvidia GTX 590 GPUs.
    • Demonstrated competitive read mapping timings compared to existing mappers using both real and simulated genomic data.
    • CORAL effectively reduces computational time and verification overhead in WGS pipelines.

    Conclusions:

    • CORAL offers an efficient solution for accelerating read mapping in genomics by leveraging heterogeneous computing.
    • The developed tool addresses scalability issues with current WGS analysis tools on modern hardware.
    • CORAL shows promise for advancing personalized and P4 medicine through faster genomic data processing.