From 3b54def58d4e7029ed091c49056e40d2e9e2ca8b Mon Sep 17 00:00:00 2001 From: akashdhruv Date: Tue, 20 Jun 2023 19:40:58 -0500 Subject: [PATCH 1/2] update paper --- paper/paper.md | 14 ++++++++++---- 1 file changed, 10 insertions(+), 4 deletions(-) diff --git a/paper/paper.md b/paper/paper.md index 0367cbf1..84306242 100644 --- a/paper/paper.md +++ b/paper/paper.md @@ -58,15 +58,21 @@ Output from Flash-X boiling simulations is created and stored on multinode clust this output through BoxKit allows for scaling a simple operation over block to a list of blocks as shown below, -``` +```python + +# Decorate function on a block +# with desired configuration for +# parallelization +@Action(num_procs, parallel_backend) def operation_on_block(block, *args): pass -Action(operation_on_block, no_of_processes, parallel_backend)( - (block for block in list_of_blocks), *args) +# Call the function with list of +# blocks as the first argument +operation_on_block((block for block in list_of_blocks), *args) ``` -The `Action` wrappers converts the function, `operation_on_block`, into a parallel method which +The `Action` wrapperer converts the function, `operation_on_block`, into a parallel method which can be deployed on a multinode cluster with the desired backend (JobLib/Dask). BoxKit does not interfere with parallelization schema of target applications like SciKit, OpticalFlow, and PyTorch which function independently using available resources. From 5d4cf77688b0484727ba8be584e920660abe3099 Mon Sep 17 00:00:00 2001 From: akashdhruv Date: Tue, 20 Jun 2023 19:43:18 -0500 Subject: [PATCH 2/2] update comments in code block --- paper/paper.md | 7 ++----- 1 file changed, 2 insertions(+), 5 deletions(-) diff --git a/paper/paper.md b/paper/paper.md index 84306242..960ec06c 100644 --- a/paper/paper.md +++ b/paper/paper.md @@ -60,15 +60,12 @@ shown below, ```python -# Decorate function on a block -# with desired configuration for -# parallelization +# Decorate function on a block with desired configuration for parallelization @Action(num_procs, parallel_backend) def operation_on_block(block, *args): pass -# Call the function with list of -# blocks as the first argument +# Call the function with list of blocks as the first argument operation_on_block((block for block in list_of_blocks), *args) ```