Workflows

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608 Workflows visible to you, out of a total of 651
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

sars-cov-2-pe-illumina-artic-variant-calling/COVID-19-PE-ARTIC-ILLUMINA

COVID-19: variation analysis on ARTIC PE data

The workflow for Illumina-sequenced ampliconic data builds on the RNASeq workflow for paired-end data using the same steps for mapping and variant calling, but adds extra logic for trimming amplicon primer sequences off reads with the ivar package. In addition, this workflow uses ivar also to identify amplicons affected by primer-binding site mutations and, if possible, excludes reads derived from such ...

Type: Galaxy

Creator: Wolfgang Maier

Submitter: WorkflowHub Bot

DOI: 10.48546/workflowhub.workflow.110.7

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

Assembly-Hifi-Trio-phasing-VGP5/main

Assembly with Hifi reads and Trio Data

Generate phased assembly based on PacBio Hifi Reads using parental Illumina data for phasing

Inputs

  1. Hifi long reads [fastq]
  2. Concatenated Illumina reads : Paternal [fastq]
  3. Concatenated Illumina reads : Maternal [fastq]
  4. K-mer database [meryldb]
  5. Paternal hapmer database [meryldb]
  6. Maternal hapmer database [meryldb]
  7. Genome profile summary generated by Genomescope [txt]
  8. Bloom Filter
  9. Name of first haplotype
  10. Name of second haplotype ...

Type: Galaxy

Creator: Galaxy, VGP

Submitter: WorkflowHub Bot

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

COMPSs GPU Cache DNN Distributed Training
Stable

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

PyTorch distributed training of CNN on GPU and leveraging COMPSs GPU Cache for deserialization speedup. Launched using 32 GPUs (16 nodes). Dataset: Imagenet Version dislib-0.9 Version PyTorch 1.7.1+cu101

Average task execution time: 36 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.802.1

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