Workflows
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Name: Matrix multiplication with Files, reproducibility example Contact Person: [email protected] Access Level: public License Agreement: Apache2 Platform: COMPSs
Description
Matrix multiplication is a binary operation that takes a pair of matrices and produces another matrix.
If A is an n×m matrix and B is an m×p matrix, the result AB of their multiplication is an n×p matrix defined only if the number of columns m in A is equal to the number of rows m in B. When multiplying ...
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:
- Performs multiple increments of input values in parallel using COMPSs.
- Concurrently calculates Fibonacci numbers using recursive COMPSs tasks.
- 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
Calculates the Fibonacci series up to a specified length.
Type: COMPSs
Creator: Uploading this Workflow under the guidance of Raül Sirvent.
Submitter: Ashish Bhawel
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
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
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
Name: K-Means GPU Cache ON Contact Person: [email protected] 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
Name: Dislib Distributed Training - Cache ON Contact Person: [email protected] 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
Name: Dislib Distributed Training - Cache OFF Contact Person: [email protected] Access Level: public License Agreement: Apache2 Platform: COMPSs Machine: Minotauro-MN4
PyTorch distributed training of CNN on GPU. Launched using 32 GPUs (16 nodes). Dataset: Imagenet Version dislib-0.9 Version PyTorch 1.7.1+cu101
Average task execution time: 84 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
Lysozyme in water full COMPSs application run at MareNostrum IV, using full dataset with two workers