Workflows

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738 Workflows visible to you, out of a total of 793
Docker ABC MD Setup tutorial
Stable

AMBER Protein MD Setup tutorials using BioExcel Building Blocks (biobb)

Based on the official GROMACS tutorial.

This tutorial aims to illustrate the process of setting up a simulation system containing a protein, step by step, using the BioExcel Building Blocks library (biobb) wrapping the Ambertools MD package.

Copyright & Licensing

This software has been developed in the MMB group ...

Type: Docker

Creators: Adam Hospital, Genís Bayarri

Submitter: Genís Bayarri

DOI: 10.48546/workflowhub.workflow.817.1

COMPSs with Incrementation and Fibonacci series example
Stable

Name: Incrementation and Fibonacci Access Level: public License Agreement: Apache2 Platform: COMPSs

Description

Brief Overview: Demonstrates COMPSs task parallelism with increment and Fibonacci computations. Helps to understand COMPSs.

Detailed Description:

  1. Performs multiple increments of input values in parallel using COMPSs.
  2. Concurrently calculates Fibonacci numbers using recursive COMPSs tasks.
  3. Demonstrates task synchronization via compss_wait_on.

Execution

...

Type: COMPSs

Creators: Ashish Bhawel, Ashish Bhawel, Uploading this Workflow under the guidance of Raül Sirvent.

Submitter: Ashish Bhawel

Stochastic Gravitational Wave Backgorund (SGWB) tool
Stable

The tool provides a calculation of the power spectrum of Stochastic Gravitational Wave Backgorund (SGWB) from a first-order cosmological phase transition based on the parameterisations of Roper Pol et al. (2023). The power spectrum includes two components: from the sound waves excited by collisions of bubbles of the new phase and from the turbulence that is induced by these collisions.

The cosmological epoch of the phase transition is described by the temperature, T_star and by the number(s) of ...

Type: Galaxy

Creators: Andrii Neronov, Théo Boyer, Denys Savchenko, Volodymyr Savchenko

Submitter: Denys Savchenko

DOI: 10.48546/workflowhub.workflow.815.2

sanger-tol/treeval v1.1.0 - Ancient Aurora
Stable

Cite with Zenodo Nextflow run with conda run with docker ...

Type: Nextflow

Creators: Damon-Lee Pointon, William Eagles, Ying Sims

Submitter: Damon-Lee Pointon

A workflow demonstrating the 'Run interpolation based on IDW' tool
No description specified

Type: Galaxy

Creators: None

Submitter: Markus Konkol

My COMPSs Fibonacci Series
Stable

Calculates the Fibonacci series up to a specified length.

Type: COMPSs

Creator: Uploading this Workflow under the guidance of Raül Sirvent.

Submitter: Ashish Bhawel

COMPSs GPU Cache Matrix Multiplication
Stable

Name: Matmul GPU Case 1 Cache-ON Contact Person: cristian.tatu@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs Machine: Minotauro-MN4

Matmul running on the GPU leveraging COMPSs GPU Cache for deserialization speedup. Launched using 32 GPUs (16 nodes). Performs C = A @ B Where A: shape (320, 56_900_000) block_size (10, 11_380_000)             B: shape (56_900_000, 10)   block_size (11_380_000, 10)             C: shape (320, 10)                block_size ...

Type: COMPSs

Creators: Cristian Tatu, The Workflows and Distributed Computing Team (https://www.bsc.es/discover-bsc/organisation/scientific-structure/workflows-and-distributed-computing/)

Submitter: Cristian Tatu

DOI: 10.48546/workflowhub.workflow.798.1

COMPSs GPU Matrix Multiplication
Stable

Name: Matmul GPU Case 1 Cache-OFF Contact Person: cristian.tatu@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs 3.3 Machine: Minotauro-MN4

Matmul running on the GPU without Cache. Launched using 32 GPUs (16 nodes). Performs C = A @ B Where A: shape (320, 56_900_000) block_size (10, 11_380_000)             B: shape (56_900_000, 10)   block_size (11_380_000, 10)             C: shape (320, 10)                block_size (10, 10) Total dataset size 291 ...

Type: COMPSs

Creators: Cristian Tatu, The Workflows and Distributed Computing Team (https://www.bsc.es/discover-bsc/organisation/scientific-structure/workflows-and-distributed-computing/)

Submitter: Cristian Tatu

DOI: 10.48546/workflowhub.workflow.797.1

COMPSs GPU K-Means
Stable

Name: K-Means GPU Cache OFF Contact Person: cristian.tatu@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs Machine: Minotauro-MN4

K-Means running on GPUs. Launched using 32 GPUs (16 nodes). Parameters used: K=40 and 32 blocks of size (1_000_000, 1200). It creates a block for each GPU. Total dataset shape is (32_000_000, 1200). Version dislib-0.9

Average task execution time: 194 seconds

Type: COMPSs

Creators: Cristian Tatu, The Workflows and Distributed Computing Team (https://www.bsc.es/discover-bsc/organisation/scientific-structure/workflows-and-distributed-computing/)

Submitter: Cristian Tatu

DOI: 10.48546/workflowhub.workflow.799.1

COMPSs GPU Cache K-Means
Stable

Name: K-Means GPU Cache ON Contact Person: cristian.tatu@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs Machine: Minotauro-MN4

K-Means running on the GPU leveraging COMPSs GPU Cache for deserialization speedup. Launched using 32 GPUs (16 nodes). Parameters used: K=40 and 32 blocks of size (1_000_000, 1200). It creates a block for each GPU. Total dataset shape is (32_000_000, 1200). Version dislib-0.9

Average task execution time: 16 seconds

Type: COMPSs

Creators: Cristian Tatu, The Workflows and Distributed Computing Team (https://www.bsc.es/discover-bsc/organisation/scientific-structure/workflows-and-distributed-computing/)

Submitter: Cristian Tatu

DOI: 10.48546/workflowhub.workflow.800.1

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