Yumechi | ゆめち

@ryanmcshane@fosstodon.org r$> getParseData(parse(text = "a = 1; f(a, x = 1)")) line1 col1 line2 col2 id parent token terminal text 9 1 1 1 5 9 0 expr_or_assign_or_help FALSE 1 1 1 1 1 1 3 SYMBOL TRUE a 3 1 1 1 1 3 9 expr FALSE 2 1 3 1 3 2 9 EQ_ASSIGN TRUE = 5 1 5 1 5 5 6 NUM_CONST TRUE 1 6 1 5 1 5 6 9 expr FALSE 7 1 6 1 6 7 0 ';' TRUE ; 28 1 8 1 18 28 0 expr FALSE 11 1 8 1 8 11 13 SYMBOL_FUNCTION_CALL TRUE f 13 1 8 1 8 13 28 expr FALSE 12 1 9 1 9 12 28 '(' TRUE ( 14 1 10 1 10 14 16 SYMBOL TRUE a 16 1 10 1 10 16 28 expr FALSE 15 1 11 1 11 15 28 ',' TRUE , 20 1 13 1 13 20 28 SYMBOL_SUB TRUE x 21 1 15 1 15 21 28 EQ_SUB TRUE = 22 1 17 1 17 22 23 NUM_CONST TRUE 1 23 1 17 1 17 23 28 expr FALSE 24 1 18 1 18 24 28 ')' TRUE )

Refining my #nextflow #cuda #GPU process for #bioinformatics , does anyone have some pointers on how to:

- Assign individual GPU IDs to docker run? The process only uses one GPU but the server may have multiple GPUs, how does each sample know which GPU ID to use?
- Is there an established way to detect CUDA versions and choose the right image? I wrote a pipeline to build and tag for every possible version but not sure how to make it happen on nextflow. https://hub.docker.com/r/l1drm/dreg/

I partially solved (2) by a hack:

https://github.com/Functional-Genomics-Lab/dREG-nf/blob/main/modules/local/dreg/main.nf

https://github.com/Functional-Genomics-Lab/dREG-nf/blob/main/bin/cuda_version.sh

@ryanmcshane@fosstodon.org @rstats@a.gup.pe@mi.yumechi.jp Not sure what is the common name for this but I did a static analysis on R packages in undergraduate project. I know in x(a = 1), = is parsed as EQ_SUB and x = 1 is parsed as EQ_ASSIGN, so I guess it implies it is called "call x substituting parameter a by 1" maybe?