Workflows

What is a Workflow?
1480 Workflows visible to you, out of a total of 1578
Work-in-progress

The input to this workflow is a data matrix of gene expression that was collected from a pediatric patient tumor patient from the KidsFirst Common Fund program [1]. The RNA-seq samples are the columns of the matrix, and the rows are the raw expression gene count for all human coding genes (Table 1). This data matrix is fed into TargetRanger [2] to screen for targets which are highly expressed in the tumor but lowly expressed across most healthy human tissues based on gene expression data collected ...

Type: Common Workflow Language

Creators: None

Submitter: Daniel Clarke

Stable

This workflow provides a calculaiton 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) ...

Type: Galaxy

Creators: Andrii Neronov, Théo Boyer

Submitter: Andrii Neronov

DOI: 10.48546/workflowhub.workflow.831.1

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

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 ...

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

No description specified

Type: Galaxy

Creators: None

Submitter: Markus Konkol

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

Stable

Name: Matmul GPU Case 1 Cache-ON Contact Person: [email protected] 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

Stable

Name: Matmul GPU Case 1 Cache-OFF Contact Person: [email protected] 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

Stable

Name: K-Means GPU Cache OFF Contact Person: [email protected] 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

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