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The --CPU flag is not helping with speed #1623
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Dear @bbitarello, Can you first clean your directory Best, |
Hello, |
Dear @bbitarello, When I install with See the difference here:
The hyphy team didn't write nor actively maintains the I can help more if installed from source. Best, |
Thank you. I think my previous installed version (which was very old) had been installed form source, and it was faster. Trying this now:
All good. Ran the tests before running make:
All the tests are successful except fel:
So I went to check the output of those tests (~/hyphy/Testing/Temporary/LastTest.log), looked for the fel test, and found:
Any ideas? This seems very strange. It works up to a certain point and fails at this specific site. I appreciate your help. Best regards |
I just realized this error I am getting above was described by someone else here. #1585 |
I went back and decided to start over by making triple sure I had all the pre-reqs installed (yes). It goes well until the "make test" phase, as before. (but, also, I noticed a feel "failed" before that regarding neon and avx extensions - what are these?). I appreciate your help `#starting over with #testing again 95% tests passed, 1 tests failed out of 20 Total Test time (real) = 605.91 sec The following tests FAILED: #once again I went to the file ~/hyphy/Testing/temporary/LastTest.log and found: ** Found 13 sites under pervasive positive diversifying and 28 sites under negative selection at p <= 0.1**Error: Function call stack |
Dear @bbitarello, You can ignore this error; it's a stochastic multi-threading issue which will be fixed in the next release. That said, for your application, it is better to use the MPI version of HyPhy (where you can spawn different processes and handle individual sites in parallel). You can make it with This is because for FEL, multi-threading does not help nearly as much as farming out individual sites to separate processes. Finally, For example, using Multi-threaded run
Single-threaded run
MPI run
Best, |
Ok, thank you. This works now. |
Hello,
I am trying to run fel with 1,000 bootstraps and I wanted to make this go faster in a mini-server (Ubuntu) with two nodes and 40 CPUs.
Running lscpu to get some system specs I get:
Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Byte Order: Little Endian Address sizes: 46 bits physical, 48 bits virtual CPU(s): 40 On-line CPU(s) list: 0-39 Thread(s) per core: 2 Core(s) per socket: 10 Socket(s): 2 NUMA node(s): 2 Vendor ID: GenuineIntel CPU family: 6 Model: 85 Model name:Intel(R) Xeon(R) Silver 4210R CPU @ 2.40GHz Stepping: 7 CPU MHz: 1000.084 CPU max MHz: 3200.0000 CPU min MHz: 1000.0000 BogoMIPS: 4800.00 Virtualization: \VT-x L1d cache: 640 KiB L1i cache: 640 KiB L2 cache: 20 MiB L3 cache: 27.5 MiB NUMA node0 CPU(s): 0-9,20-29 NUMA node1 CPU(s): 10-19,30-39
All the tests below were run on a dataset consisting of one gene (~ 300 codons) and 54 primate species.
Command:
hyphy FEL --code Universal --alignment "${alg_file}" --tree "${tree_file}" --branches All --srv Yes --pvalue 0.1 --ci No --output "${json_file}" --precision standard --full-model Yes
Command:
hyphy FEL --code Universal --alignment "${alg_file}" --tree "${tree_file}" --branches All --srv Yes --pvalue 0.1 --ci Yes --resample 20 --output "${json_file}" --precision standard --full-model Yes --CPU 1
Command:
hyphy FEL --code Universal --alignment "${alg_file}" --tree "${tree_file}" --branches All --srv Yes --pvalue 0.1 --ci Yes --resample 20 --output "${json_file}" --precision standard --full-model Yes --CPU 2
hyphy FEL --code Universal --alignment "${alg_file}" --tree "${tree_file}" --branches All --srv Yes --pvalue 0.1 --ci Yes --resample 20 --output "${json_file}" --precision standard --full-model Yes --CPU 4
grep benchmark
messages.log. Result:Auto-benchmarked an optimal number (1) of threads. Auto-benchmarked an optimal number (4) of threads. Auto-benchmarked an optimal number (5) of threads. Auto-benchmarked an optimal number (3) of threads. Auto-benchmarked an optimal number (7) of threads. Auto-benchmarked an optimal number (4) of threads. Auto-benchmarked an optimal number (7) of threads.
Questions:
Thank you!
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