Posts by Azmodes

1) Message boards : Server and website : Undying task (Message 59227) Posted 11 Sep 2022 by Azmodes Post: Only the project admins have access to the server database. Right, so it's never gonna happen.
2) Message boards : Server and website : Undying task (Message 59196) Posted 6 Sep 2022 by Azmodes Post: Anyone?
3) Message boards : News : Experimental Python tasks (beta) - task description (Message 58618) Posted 11 Apr 2022 by Azmodes Post: Same.
4) Message boards : Server and website : Undying task (Message 58507) Posted 13 Mar 2022 by Azmodes Post: It's a minor nuisance, but I've had this tenacious little fella listed in my tasks for over three years now. Any way to remove it? :)
5) Message boards : News : ACEMD 4 (Message 58429) Posted 4 Mar 2022 by Azmodes Post: Thanks for the explanation, RH. :) Getting validating acemd4 tasks now.
6) Message boards : News : ACEMD 4 (Message 58424) Posted 4 Mar 2022 by Azmodes Post: ah, so the failing tasks are actually acemd3? I'm not sure what that disk limit error is about. All my relevant hosts are set to allow between 30-75 GB of space for BOINC. The event logs confirm this setting. Also, unrelated and nothing new, but this site is such a supreme pain in the butt to navigate if you are running multiple hosts from the same external IP... Ridiculous.
7) Message boards : News : ACEMD 4 (Message 58420) Posted 4 Mar 2022 by Azmodes Post: My hosts received WUs, but they error out after 5 minutes: <core_client_version>7.16.6</core_client_version> <![CDATA[ <message> process exited with code 195 (0xc3, -61)</message> <stderr_txt> 14:39:40 (150677): wrapper (7.7.26016): starting 14:39:40 (150677): wrapper (7.7.26016): starting 14:39:40 (150677): wrapper: running /bin/tar (xf x86_64-pc-linux-gnu__cuda1121.tar.bz2) 14:44:45 (150677): /bin/tar exited; CPU time 299.093084 14:44:45 (150677): wrapper: running bin/acemd (--boinc --device 0) ERROR: /home/user/conda/conda-bld/acemd_1646158992086/work/src/mdio/amberparm.cpp line 76: Unsupported PRMTOP version! 14:44:46 (150677): bin/acemd exited; CPU time 0.205850 14:44:46 (150677): app exit status: 0x9e 14:44:46 (150677): called boinc_finish(195) </stderr_txt> ]]> I noticed that the only ones failing are v1.02. v2.19 ones validate (well, one did so far, the rest are still running). I'm a bit confused, so is v1 ACEMD 3 and v2 ACEMD 4? Or are both different versions of ACEMD 4?
8) Message boards : News : Python Runtime (GPU, beta) (Message 57727) Posted 3 Nov 2021 by Azmodes Post: Got one that ended in 195 (0xc3) EXIT_CHILD_FAILED after 15 minutes: ==> WARNING: A newer version of conda exists. <== current version: 4.8.3 latest version: 4.10.3 Please update conda by running $ conda update -n base -c defaults conda 13:14:06 (11501): /usr/bin/flock exited; CPU time 470.306190 13:14:06 (11501): wrapper: running ./gpugridpy/bin/python (run.py) path: ['/var/lib/boinc-client/slots/34', '/var/lib/boinc-client/slots/34/gpugridpy/lib/python3.8/site-packages/git/ext/gitdb', '/var/lib/boinc-client/slots/34/gpugridpy/lib/python38.zip', '/var/lib/boinc-client/slots/34/gpugridpy/lib/python3.8', '/var/lib/boinc-client/slots/34/gpugridpy/lib/python3.8/lib-dynload', '/var/lib/boinc-client/slots/34/gpugridpy/lib/python3.8/site-packages', '/var/lib/boinc-client/slots/34/gpugridpy/lib/python3.8/site-packages/gitdb/ext/smmap'] git path: /var/lib/boinc-client/slots/34/gpugridpy/lib/python3.8/site-packages/git Traceback (most recent call last): File "run.py", line 340, in <module> main() File "run.py", line 53, in main print("GPU available: {}".format(torch.cuda.is_available())) NameError: name 'torch' is not defined 13:14:10 (11501): ./gpugridpy/bin/python exited; CPU time 1.602758 13:14:10 (11501): app exit status: 0x1 13:14:10 (11501): called boinc_finish(195) </stderr_txt> ]]>
9) Message boards : News : Python Runtime (GPU, beta) (Message 57706) Posted 1 Nov 2021 by Azmodes Post: So, uh, that was it?
10) Message boards : News : Python Runtime (GPU, beta) (Message 57660) Posted 26 Oct 2021 by Azmodes Post: Got a 2080 Ti and two 2070 Supers ready to roll.
11) Message boards : News : Python Runtime (GPU, beta) (Message 57657) Posted 26 Oct 2021 by Azmodes Post: GPUGRID 10/26/2021 2:01:26 PM No tasks are available for Python apps for GPU hosts
12) Message boards : Number crunching : Anaconda Python 3 Environment v4.01 failures (Message 56178) Posted 29 Dec 2020 by Azmodes Post: I'll be removing this for the time being. Been getting a lot of tasks that error out after hours, lots of wasted computing time.
13) Message boards : Number crunching : Anaconda Python 3 Environment v4.01 failures (Message 56164) Posted 28 Dec 2020 by Azmodes Post: Been getting "1 (0x1) Unknown error number" after a couple of minutes on a few of my machines (one of which also had valid ones a few days ago). Is this something on my end? <core_client_version>7.16.6</core_client_version> <![CDATA[ <message> process exited with code 1 (0x1, -255)</message> <stderr_txt> 12:51:44 (69060): wrapper (7.7.26016): starting 12:51:44 (69060): wrapper (7.7.26016): starting 12:51:44 (69060): wrapper: running /usr/bin/flock (/var/lib/boinc-client/projects/www.gpugrid.net/miniconda.lock -c "/bin/bash ./miniconda-installer.sh -b -u -p /var/lib/boinc-client/projects/www.gpugrid.net/miniconda && /var/lib/boinc-client/projects/www.gpugrid.net/miniconda/bin/conda install -m -y -p gpugridpy --file requirements.txt ") 0%\| \| 0/96 [00:00<?, ?it/s] Extracting : libgcc-ng-9.1.0-hdf63c60_0.conda: 0%\| \| 0/96 [00:00<?, ?it/s] Extracting : libgcc-ng-9.1.0-hdf63c60_0.conda: 1%\|1 \| 1/96 [00:00<00:23, 4.13it/s] Extracting : tk-8.6.8-hbc83047_0.conda: 1%\|1 \| 1/96 [00:00<00:23, 4.13it/s] Extracting : setuptools-46.4.0-py37_0.conda: 2%\|2 \| 2/96 [00:00<00:22, 4.13it/s] Extracting : requests-2.23.0-py37_0.conda: 3%\|3 \| 3/96 [00:00<00:22, 4.13it/s] Extracting : cudnn-7.6.5-cuda10.2_0.conda: 4%\|4 \| 4/96 [03:04<00:22, 4.13it/s] Extracting : cudnn-7.6.5-cuda10.2_0.conda: 5%\|5 \| 5/96 [03:04<21:12, 13.99s/it] Extracting : numpy-1.19.2-py37h54aff64_0.conda: 5%\|5 \| 5/96 [03:04<21:12, 13.99s/it] Extracting : pysocks-1.7.1-py37_0.conda: 6%\|6 \| 6/96 [03:04<20:59, 13.99s/it] Extracting : cffi-1.14.0-py37he30daa8_1.conda: 7%\|7 \| 7/96 [03:04<20:45, 13.99s/it] Extracting : conda-package-handling-1.6.1-py37h7b6447c_0.conda: 8%\|8 \| 8/96 [03:04<20:31, 13.99s/it] Extracting : pycosat-0.6.3-py37h7b6447c_0.conda: 9%\|9 \| 9/96 [03:04<20:17, 13.99s/it] Extracting : wheel-0.34.2-py37_0.conda: 10%\|# \| 10/96 [03:04<20:03, 13.99s/it] Extracting : libedit-3.1.20181209-hc058e9b_0.conda: 11%\|#1 \| 11/96 [03:04<19:49, 13.99s/it] Extracting : sqlite-3.31.1-h62c20be_1.conda: 12%\|#2 \| 12/96 [03:04<19:35, 13.99s/it] Extracting : libstdcxx-ng-9.1.0-hdf63c60_0.conda: 14%\|#3 \| 13/96 [03:04<19:21, 13.99s/it] Extracting : chardet-3.0.4-py37_1003.conda: 15%\|#4 \| 14/96 [03:04<19:07, 13.99s/it] Extracting : readline-8.0-h7b6447c_0.conda: 16%\|#5 \| 15/96 [03:04<18:53, 13.99s/it] Extracting : python-3.7.7-hcff3b4d_5.conda: 17%\|#6 \| 16/96 [03:04<18:39, 13.99s/it] Extracting : libffi-3.3-he6710b0_1.conda: 18%\|#7 \| 17/96 [03:04<18:25, 13.99s/it] Extracting : pip-20.0.2-py37_3.conda: 19%\|#8 \| 18/96 [03:04<18:11, 13.99s/it] Extracting : pyopenssl-19.1.0-py37_0.conda: 20%\|#9 \| 19/96 [03:04<17:57, 13.99s/it] Extracting : _libgcc_mutex-0.1-main.conda: 21%\|## \| 20/96 [03:04<17:43, 13.99s/it] Extracting : urllib3-1.25.8-py37_0.conda: 22%\|##1 \| 21/96 [03:04<17:29, 13.99s/it] Extracting : blas-1.0-mkl.conda: 23%\|##2 \| 22/96 [03:04<17:15, 13.99s/it] Extracting : certifi-2020.4.5.1-py37_0.conda: 24%\|##3 \| 23/96 [03:04<17:01, 13.99s/it] Extracting : scipy-1.5.2-py37h0b6359f_0.conda: 25%\|##5 \| 24/96 [03:04<16:47, 13.99s/it] Extracting : six-1.14.0-py37_0.conda: 26%\|##6 \| 25/96 [03:04<16:33, 13.99s/it] Extracting : idna-2.9-py_1.conda: 27%\|##7 \| 26/96 [03:04<16:19, 13.99s/it] Extracting : ncurses-6.2-he6710b0_1.conda: 28%\|##8 \| 27/96 [03:04<16:05, 13.99s/it] Extracting : zlib-1.2.11-h7b6447c_3.conda: 29%\|##9 \| 28/96 [03:04<15:51, 13.99s/it] Extracting : ld_impl_linux-64-2.33.1-h53a641e_7.conda: 30%\|### \| 29/96 [03:04<15:37, 13.99s/it] Extracting : xz-5.2.5-h7b6447c_0.conda: 31%\|###1 \| 30/96 [03:04<15:23, 13.99s/it] Extracting : ca-certificates-2020.1.1-0.conda: 32%\|###2 \| 31/96 [03:04<15:09, 13.99s/it] Extracting : tqdm-4.46.0-py_0.conda: 33%\|###3 \| 32/96 [03:04<14:55, 13.99s/it] Extracting : pycparser-2.20-py_0.conda: 34%\|###4 \| 33/96 [03:04<14:41, 13.99s/it] Extracting : openssl-1.1.1g-h7b6447c_0.conda: 35%\|###5 \| 34/96 [03:04<14:27, 13.99s/it] Extracting : cudatoolkit-10.2.89-hfd86e86_1.conda: 36%\|###6 \| 35/96 [03:40<14:13, 13.99s/it] Extracting : cudatoolkit-10.2.89-hfd86e86_1.conda: 38%\|###7 \| 36/96 [03:40<10:08, 10.14s/it] Extracting : yaml-0.1.7-had09818_2.conda: 38%\|###7 \| 36/96 [03:40<10:08, 10.14s/it] Extracting : ruamel_yaml-0.15.87-py37h7b6447c_0.conda: 39%\|###8 \| 37/96 [03:40<09:58, 10.14s/it] Extracting : numpy-base-1.19.2-py37hfa32c7d_0.conda: 40%\|###9 \| 38/96 [03:40<09:47, 10.14s/it] Extracting : cryptography-2.9.2-py37h1ba5d50_0.conda: 41%\|#### \| 39/96 [03:40<09:37, 10.14s/it] Extracting : ncurses-6.2-h58526e2_3.tar.bz2: 42%\|####1 \| 40/96 [03:40<09:27, 10.14s/it] Extracting : libstdcxx-ng-9.3.0-h2ae2ef3_17.tar.bz2: 43%\|####2 \| 41/96 [03:40<09:17, 10.14s/it] Extracting : cffi-1.14.3-py37h00ebd2e_1.tar.bz2: 44%\|####3 \| 42/96 [03:40<09:07, 10.14s/it] Extracting : networkx-2.5-py_0.tar.bz2: 45%\|####4 \| 43/96 [03:40<08:57, 10.14s/it] Extracting : libffi-3.2.1-he1b5a44_1007.tar.bz2: 46%\|####5 \| 44/96 [03:40<08:47, 10.14s/it] Extracting : libllvm10-10.0.1-he513fc3_3.tar.bz2: 47%\|####6 \| 45/96 [03:40<08:36, 10.14s/it] Extracting : mkl-2020.4-h726a3e6_304.tar.bz2: 48%\|####7 \| 46/96 [03:40<08:26, 10.14s/it] Extracting : brotlipy-0.7.0-py37hb5d75c8_1001.tar.bz2: 49%\|####8 \| 47/96 [03:40<08:16, 10.14s/it] Extracting : six-1.15.0-pyh9f0ad1d_0.tar.bz2: 50%\|##### \| 48/96 [03:40<08:06, 10.14s/it] Extracting : sqlite-3.33.0-h4cf870e_1.tar.bz2: 51%\|#####1 \| 49/96 [03:40<07:56, 10.14s/it] Extracting : xz-5.2.5-h516909a_1.tar.bz2: 52%\|#####2 \| 50/96 [03:40<07:46, 10.14s/it] Extracting : mkl_fft-1.2.0-py37h161383b_1.tar.bz2: 53%\|#####3 \| 51/96 [03:40<07:36, 10.14s/it] Extracting : urllib3-1.25.11-py_0.tar.bz2: 54%\|#####4 \| 52/96 [03:40<07:25, 10.14s/it] Extracting : conda-4.8.3-py37_0.tar.bz2: 55%\|#####5 \| 53/96 [03:40<07:15, 10.14s/it] Extracting : mkl_random-1.2.0-py37h9fdb41a_1.tar.bz2: 56%\|#####6 \| 54/96 [03:40<07:05, 10.14s/it] Extracting : lark-parser-0.10.0-pyh9f0ad1d_0.tar.bz2: 57%\|#####7 \| 55/96 [03:40<06:55, 10.14s/it] Extracting : zlib-1.2.11-h516909a_1010.tar.bz2: 58%\|#####8 \| 56/96 [03:40<06:45, 10.14s/it] Extracting : wheel-0.35.1-pyh9f0ad1d_0.tar.bz2: 59%\|#####9 \| 57/96 [03:40<06:35, 10.14s/it] Extracting : tqdm-4.51.0-pyh9f0ad1d_0.tar.bz2: 60%\|###### \| 58/96 [03:40<06:25, 10.14s/it] Extracting : libgcc-ng-9.3.0-h5dbcf3e_17.tar.bz2: 61%\|######1 \| 59/96 [03:40<06:15, 10.14s/it] Extracting : _libgcc_mutex-0.1-conda_forge.tar.bz2: 62%\|######2 \| 60/96 [03:40<06:04, 10.14s/it] Extracting : numba-0.51.2-py37h9fdb41a_0.tar.bz2: 64%\|######3 \| 61/96 [03:40<05:54, 10.14s/it] Extracting : llvmlite-0.34.0-py37h5202443_2.tar.bz2: 65%\|######4 \| 62/96 [03:40<05:44, 10.14s/it] Extracting : certifi-2020.6.20-py37he5f6b98_2.tar.bz2: 66%\|######5 \| 63/96 [03:40<05:34, 10.14s/it] Extracting : torchani-2.2-pyh9f0ad1d_0.tar.bz2: 67%\|######6 \| 64/96 [03:40<05:24, 10.14s/it] Extracting : ld_impl_linux-64-2.35-h769bd43_9.tar.bz2: 68%\|######7 \| 65/96 [03:40<05:14, 10.14s/it] Extracting : pycparser-2.20-pyh9f0ad1d_2.tar.bz2: 69%\|######8 \| 66/96 [03:40<05:04, 10.14s/it] Extracting : ca-certificates-2020.11.8-ha878542_0.tar.bz2: 70%\|######9 \| 67/96 [03:40<04:53, 10.14s/it] Extracting : pysocks-1.7.1-py37he5f6b98_2.tar.bz2: 71%\|####### \| 68/96 [03:40<04:43, 10.14s/it] Extracting : cryptography-3.2.1-py37hc72a4ac_0.tar.bz2: 72%\|#######1 \| 69/96 [03:40<04:33, 10.14s/it] Extracting : python-dateutil-2.8.1-py_0.tar.bz2: 73%\|#######2 \| 70/96 [03:40<04:23, 10.14s/it] Extracting : acemd3-3.3.0-cuda100_0.tar.bz2: 74%\|#######3 \| 71/96 [03:40<04:13, 10.14s/it] Extracting : tk-8.6.10-hed695b0_1.tar.bz2: 75%\|#######5 \| 72/96 [03:40<04:03, 10.14s/it] Extracting : mkl-service-2.3.0-py37h8f50634_2.tar.bz2: 76%\|#######6 \| 73/96 [03:40<03:53, 10.14s/it] Extracting : _openmp_mutex-4.5-1_llvm.tar.bz2: 77%\|#######7 \| 74/96 [03:40<03:42, 10.14s/it] Extracting : readline-8.0-he28a2e2_2.tar.bz2: 78%\|#######8 \| 75/96 [03:40<03:32, 10.14s/it] Extracting : decorator-4.4.2-py_0.tar.bz2: 79%\|#######9 \| 76/96 [03:40<03:22, 10.14s/it] Extracting : python_abi-3.7-1_cp37m.tar.bz2: 80%\|######## \| 77/96 [03:40<03:12, 10.14s/it] Extracting : setuptools-49.6.0-py37he5f6b98_2.tar.bz2: 81%\|########1 \| 78/96 [03:40<03:02, 10.14s/it] Extracting : libgfortran4-7.5.0-hae1eefd_17.tar.bz2: 82%\|########2 \| 79/96 [03:40<02:52, 10.14s/it] Extracting : acemd3-3.3.0_72_gcceda4a-cuda102_0.tar.bz2: 83%\|########3 \| 80/96 [03:40<02:42, 10.14s/it] Extracting : ninja-1.10.1-hfc4b9b4_2.tar.bz2: 84%\|########4 \| 81/96 [03:40<02:32, 10.14s/it] Extracting : idna-2.10-pyh9f0ad1d_0.tar.bz2: 85%\|########5 \| 82/96 [03:40<02:21, 10.14s/it] Extracting : requests-2.24.0-pyh9f0ad1d_0.tar.bz2: 86%\|########6 \| 83/96 [03:40<02:11, 10.14s/it] Extracting : openssl-1.1.1h-h516909a_0.tar.bz2: 88%\|########7 \| 84/96 [03:40<02:01, 10.14s/it] Extracting : pytorch-1.6.0-py3.7_cuda10.2.89_cudnn7.6.5_0.tar.bz2: 89%\|########8 \| 85/96 [04:56<01:51, 10.14s/it] Extracting : pytorch-1.6.0-py3.7_cuda10.2.89_cudnn7.6.5_0.tar.bz2: 90%\|########9 \| 86/96 [04:56<01:15, 7.55s/it] Extracting : pytz-2020.4-pyhd8ed1ab_0.tar.bz2: 90%\|########9 \| 86/96 [04:56<01:15, 7.55s/it] Extracting : nnpops-pytorch-0.0.0a3-0.tar.bz2: 91%\|######### \| 87/96 [04:56<01:07, 7.55s/it] Extracting : chardet-3.0.4-py37he5f6b98_1008.tar.bz2: 92%\|#########1\| 88/96 [04:56<01:00, 7.55s/it] Extracting : pip-20.2.4-py_0.tar.bz2: 93%\|#########2\| 89/96 [04:56<00:52, 7.55s/it] Extracting : pandas-1.1.4-py37h10a2094_0.tar.bz2: 94%\|#########3\| 90/96 [04:56<00:45, 7.55s/it] Extracting : libgfortran-ng-7.5.0-hae1eefd_17.tar.bz2: 95%\|#########4\| 91/96 [04:56<00:37, 7.55s/it] Extracting : llvm-openmp-11.0.0-hfc4b9b4_1.tar.bz2: 96%\|#########5\| 92/96 [04:56<00:30, 7.55s/it] Extracting : moleculekit-0.4.4-py37_0.tar.bz2: 97%\|#########6\| 93/96 [04:56<00:22, 7.55s/it] Extracting : python-3.7.8-h6f2ec95_1_cpython.tar.bz2: 98%\|#########7\| 94/96 [04:56<00:15, 7.55s/it] Extracting : pyopenssl-19.1.0-py_1.tar.bz2: 99%\|#########8\| 95/96 [04:56<00:07, 7.55s/it] 12:56:52 (69060): /usr/bin/flock exited; CPU time 141.751422 application ./gpugridpy/bin/python missing </stderr_txt> ]]>
14) Message boards : Number crunching : Coronavirus crunching - Folding@home (Message 54329) Posted 14 Apr 2020 by Azmodes Post: so many GPU can be counted towards computing power without getting a hold onto a work unit. That's not how it works. Like with BOINC, the processing power estimate is based on actual returned work, not registered hardware in the system. So yes, they did break that barrier and if they managed to get enough servers up to completely saturate every connected host, it should be considerably higher still. See https://stats.foldingathome.org/os
15) Message boards : News : Experiment queue being filled up (Message 53950) Posted 19 Mar 2020 by Azmodes Post: PPS sieve over at PrimeGrid will work on that.
16) Message boards : GPUGRID CAFE : Corona Virus (Message 53845) Posted 4 Mar 2020 by Azmodes Post: Rosetta@Home and Folding@Home are currently doing work related to it.
17) Message boards : Number crunching : How to write app info for the current application? (Message 53760) Posted 25 Feb 2020 by Azmodes Post: Does that actually help, though? I haven't seen any obvious improvement, at least not on Windows.
18) Message boards : Number crunching : RTX performance on Windows (Message 53755) Posted 23 Feb 2020 by Azmodes Post: I have PCI-E 2.0 Err, nevermind me, it's 3.0, durr
19) Message boards : Number crunching : RTX performance on Windows (Message 53743) Posted 22 Feb 2020 by Azmodes Post: Hm okay then, now I got a WU that's running around 90% on the RTX.
20) Message boards : Number crunching : RTX performance on Windows (Message 53731) Posted 21 Feb 2020 by Azmodes Post: It happens if you have different GPUs in the same system, and the task restarts on a different GPU than it was running before. To avoid this you should suspend the queued GPUGrid tasks first, then the running GPUGrid tasks one by one, and make note which GPU became unused before you suspend the next running task. After restart first you should resume the task which was running on device 0, then the task was running on device 1 and so on, then the unprocessed tasks. ah right, gotcha. I remember it resuming on a different GPU being the problem now. It's usually the result of an overcomitted CPU. Depending on the other (CPU+GPU) tasks running it is advised to reduce the number of simultaneous CPU tasks to the number of CPU cores (50% of CPUs in BOINC manager / Computing settings), or even less. High core count CPUs (AMD Threadripper, Intel i9-9900, AMD Ryzen 9 3950x) can use up their memory bandwidth when many CPU tasks are running simultaneously, even with 4 channel memory. This result in increased runtime of the CPU app, and reduced performance of the GPU app. I set cores used to 50% and the RTX load went up by maybe 1-2%. Setting it even lower adds maybe another percent, adding up to a whoopin' 82% for this particular WU. Running Rosetta on CPU right now, which I guess it quite memory intensive, but I was doing more forgiving stuff previously too and GPU usage was the same. Reduced PCIe bandwidth can also be the cause of reduced GPUGrid performance. CPUs with 20 PCIe lanes can't provide PCIe 3.0 x16 for all GPUs in a multi-GPU setup. I have PCI-E 2.0, three cards. Bus load is below 10% for the RTX anyway. The 1950X has 64 lanes, apparently? The other factor is the atom count of the given simulation - we don't have any info on that with the new GPUGrid app - but I think the present batch has low atom count, and it can cause lower GPU utilization on high-end GPUs. The third factor is the host OS: Linux tends to be faster (however the previous batch was just as fast on Windows). I see 89% GPU (RTX 2080Ti) usage under Windows 10, while 97-98% GPU (RTX 2080Ti) usage under Linux. I think best I got so far was maybe 85%.

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