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Related Concept Videos

Parallel Processing01:20

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...
Distributed Loads01:19

Distributed Loads

Distributed loads are a common type of load that engineers and scientists encounter in various practical situations. Distributed loads often refer to a type of load spread over a surface or a structure and can be modeled as continuous force per unit area.
For example, consider a bookshelf filled with books stacked vertically adjacent to each other. The weight of the books is evenly distributed over the length of the shelf. As a result, the pressure at different locations on the surface of the...
Distributed Loads: Problem Solving01:21

Distributed Loads: Problem Solving

Beams are structural elements commonly employed in engineering applications requiring different load-carrying capacities. The first step in analyzing a beam under a distributed load is to simplify the problem by dividing the load into smaller regions, which allows one to consider each region separately and calculate the magnitude of the equivalent resultant load acting on each portion of the beam. The magnitude of the equivalent resultant load for each region can be determined by calculating...
Quarrying of Stone01:15

Quarrying of Stone

Quarrying is the process of extracting stone from a quarry, where specialized techniques are employed to remove large blocks of stone safely and efficiently. This process can involve controlled explosions or more precision-oriented methods such as cutting and drilling.
One common method involves using a diamond belt saw to cut large blocks from the quarry face. These blocks can be about 50 feet long and 12 feet high. After the initial vertical cut, drilling is performed at the base of the block.
Downstream Processing01:29

Downstream Processing

Downstream processing begins once fermentation is complete and involves a series of steps to recover and purify products such as acids, vitamins, antibiotics, or proteins.Cell HarvestingFor example, for intracellular protein-based products, the first step is harvesting the cells. This is typically achieved using centrifugation or filtration to separate the cells from the liquid phase.Cell Disruption for Intracellular ProductsIf the target product is intracellular, the harvested cells must be...
Restarting Stalled Replication Forks02:37

Restarting Stalled Replication Forks

DNA replication is initiated at sites containing predefined DNA sequences known as origins of replication. DNA is unwound at these sites by the minichromosome maintenance (MCM) helicase and other factors such as Cdc45 and the associated GINS complex.The unwound single strands are protected by replication protein A (RPA) until DNA polymerase starts synthesizing DNA at the 5’ end of the strand in the same direction as the replication fork. To prevent the replication fork from falling apart, a...

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Operation of the Collaborative Composite Manufacturing (CCM) System
10:09

Operation of the Collaborative Composite Manufacturing (CCM) System

Published on: October 1, 2019

PAR: a PARallel and distributed job crusher.

Francois Berenger1, Camille Coti, Kam Y J Zhang

  • 1Zhang Initiative Research Unit, Advanced Science Institute, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan. berenger@riken.jp

Bioinformatics (Oxford, England)
|September 28, 2010
PubMed
Summary
This summary is machine-generated.

Bioinformaticians face complex computational challenges. The new PAR engine offers a scalable, dynamic, parallel, and distributed solution for Bag-of-Tasks applications on multi-core systems.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • High-Performance Computing

Background:

  • Bioinformaticians encounter increasingly computation-intensive tasks.
  • Workstations are evolving towards multi-core architectures, with massively multi-core systems becoming prevalent.
  • Bag-of-Tasks (BoT) applications, comprising numerous independent, computation-intensive tasks, are common in bioinformatics.

Purpose of the Study:

  • Introduce PAR, a novel execution engine for Bag-of-Tasks applications.
  • Design PAR to be scalable, dynamic, parallel, and distributed.
  • Target PAR for multi-core architectures and small clusters.

Main Methods:

  • Developed a parallel and distributed execution engine named PAR.
  • Designed PAR to handle a large number of independent computational tasks.
  • Evaluated PAR's performance on two distinct bioinformatics applications.

Main Results:

  • Demonstrated accelerations achieved using the PAR engine.
  • Showcased PAR's effectiveness on multi-core architectures.
  • Validated PAR's capability in handling Bag-of-Tasks workloads.

Conclusions:

  • PAR provides an effective solution for accelerating computation-intensive bioinformatics tasks.
  • The engine is suitable for modern multi-core workstations and small clusters.
  • PAR enhances the efficiency of Bag-of-Tasks applications in bioinformatics.