payload: {"action":"created","issue":{"url":"https://api.github.com/repos/uwplse/herbgrind/issues/32","repository_url":"https://api.github.com/repos/uwplse/herbgrind","labels_url":"https://api.github.com/repos/uwplse/herbgrind/issues/32/labels{/name}","comments_url":"https://api.github.com/repos/uwplse/herbgrind/issues/32/comments","events_url":"https://api.github.com/repos/uwplse/herbgrind/issues/32/events","html_url":"https://github.com/uwplse/herbgrind/issues/32","id":346289251,"node_id":"MDU6SXNzdWUzNDYyODkyNTE=","number":32,"title":"Not able to run spec gromacs","user":{"login":"sangeeta0201","id":33879368,"node_id":"MDQ6VXNlcjMzODc5MzY4","avatar_url":"https://avatars2.githubusercontent.com/u/33879368?v=4","gravatar_id":"","url":"https://api.github.com/users/sangeeta0201","html_url":"https://github.com/sangeeta0201","followers_url":"https://api.github.com/users/sangeeta0201/followers","following_url":"https://api.github.com/users/sangeeta0201/following{/other_user}","gists_url":"https://api.github.com/users/sangeeta0201/gists{/gist_id}","starred_url":"https://api.github.com/users/sangeeta0201/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/sangeeta0201/subscriptions","organizations_url":"https://api.github.com/users/sangeeta0201/orgs","repos_url":"https://api.github.com/users/sangeeta0201/repos","events_url":"https://api.github.com/users/sangeeta0201/events{/privacy}","received_events_url":"https://api.github.com/users/sangeeta0201/received_events","type":"User","site_admin":false},"labels":[],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":7,"created_at":"2018-07-31T17:38:09Z","updated_at":"2019-11-13T07:04:47Z","closed_at":"2019-11-12T18:12:15Z","author_association":"NONE","body":"Hi Alex,\r\n\r\nI am trying to run herbgrind with spec bechmark gromacs and I am getting seg fault. Let me know if you need any other info to reproduce this issue. \r\nI have used following command to create a gromacs binary and then manually run it using herbgrind\r\n```\r\nrunspec --config=Sangeeta-linux.cfg --size=ref --noreportable --tune=base --iterations=1 gromacs\r\n```\r\n\r\n```\r\nherbgrind.sh ./gromacs_base.gcc43-64bit -deffnm gromacs -nice 0> gromacs.ref.out 2 >gromacs.ref.err\r\n==29987== Herbgrind, a valgrind tool for Herbie\r\n==29987== Copyright (C) 2016-2017, and GNU GPL'd, by Alex Sanchez-Stern\r\n==29987== Using Valgrind-3.12.0.SVN and LibVEX; rerun with -h for copyright info\r\n==29987== Command: ./gromacs_base.gcc43-64bit -deffnm gromacs -nice 2\r\n==29987== \r\n==29987== \r\n==29987== Process terminating with default action of signal 11 (SIGSEGV)\r\n==29987==  Access not within mapped region at address 0x3FF00000\r\n==29987==    at 0x4033BB: flincs_ (in benchspec/CPU2006/435.gromacs/run/run_base_ref_gcc43-64bit.0000/gromacs_base.gcc43-64bit)\r\n==29987==    by 0x43D01B: constrain_lincs.isra.3 (constr.c:333)\r\n==29987==    by 0x43E6A4: constrain (constr.c:574)\r\n==29987==    by 0x4B251B: update (update.c:759)\r\n==29987==    by 0x49AC9C: do_shakefirst (sim_util.c:420)\r\n==29987==    by 0x46AB9A: do_md (md.c:331)\r\n==29987==    by 0x46B672: mdrunner (md.c:179)\r\n==29987==    by 0x4024BF: main (mdrun.c:235)\r\n==29987==  If you believe this happened as a result of a stack\r\n==29987==  overflow in your program's main thread (unlikely but\r\n==29987==  possible), you can try to increase the size of the\r\n==29987==  main thread stack using the --main-stacksize= flag.\r\n==29987==  The main thread stack size used in this run was 8388608.\r\n==29987== \r\nDidn't find any marks!\r\nherbgrind/herbgrind.sh: line 17: 29987 Segmentation fault      (core dumped) $HG \"$@\"\r\n```"},"comment":{"url":"https://api.github.com/repos/uwplse/herbgrind/issues/comments/553268959","html_url":"https://github.com/uwplse/herbgrind/issues/32#issuecomment-553268959","issue_url":"https://api.github.com/repos/uwplse/herbgrind/issues/32","id":553268959,"node_id":"MDEyOklzc3VlQ29tbWVudDU1MzI2ODk1OQ==","user":{"login":"jtarango","id":41123949,"node_id":"MDQ6VXNlcjQxMTIzOTQ5","avatar_url":"https://avatars0.githubusercontent.com/u/41123949?v=4","gravatar_id":"","url":"https://api.github.com/users/jtarango","html_url":"https://github.com/jtarango","followers_url":"https://api.github.com/users/jtarango/followers","following_url":"https://api.github.com/users/jtarango/following{/other_user}","gists_url":"https://api.github.com/users/jtarango/gists{/gist_id}","starred_url":"https://api.github.com/users/jtarango/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/jtarango/subscriptions","organizations_url":"https://api.github.com/users/jtarango/orgs","repos_url":"https://api.github.com/users/jtarango/repos","events_url":"https://api.github.com/users/jtarango/events{/privacy}","received_events_url":"https://api.github.com/users/jtarango/received_events","type":"User","site_admin":false},"created_at":"2019-11-13T07:04:47Z","updated_at":"2019-11-13T07:04:47Z","author_association":"NONE","body":"Just for a point of reference. When I am tracking time series for herbgrind, I have switched some computation to float vs double then rand the computation on terabytes of data. For a data point today, I peaked my virtual machine DRAM at 64 GB and ~68 GB of swap space... Valgrind takes quite a bit of memory when tracking the long computation chains. To enable this temporarily, you will have to do the items above with ulimit -s unlimited to set an unlimited stack. \r\n\r\nTo enable valgrind with unlimited resources, I had to enable an unlimited stack.\r\n[jtarango@] $ ulimit -a\r\ncore file size          (blocks, -c) 0\r\ndata seg size           (kbytes, -d) unlimited\r\nscheduling priority             (-e) 0\r\nfile size               (blocks, -f) unlimited\r\npending signals                 (-i) 257347\r\nmax locked memory       (kbytes, -l) 16384\r\nmax memory size         (kbytes, -m) unlimited\r\nopen files                      (-n) 1024\r\npipe size            (512 bytes, -p) 8\r\nPOSIX message queues     (bytes, -q) 819200\r\nreal-time priority              (-r) 0\r\nstack size              (kbytes, -s) unlimited\r\ncpu time               (seconds, -t) unlimited\r\nmax user processes              (-u) unlimited\r\nvirtual memory          (kbytes, -v) unlimited\r\nfile locks                      (-x) unlimited\r\n\r\nIf anyone is doing Machine Learning and Artificial intelligence big data computation, I recommend to switch to an Intel Purley platform with with the maxima memory configuration I.E. 12TB of Optane DIMMs may be installed in a quad-socket system (3TB per CPU + 1.5TB of DRAM). Then to get above the runtime memory limit, I recommend to have a large ZFS pool with a swap as large as the application needs. For applications such as genetics, you will need 1 petabyte of swap space to be able to do large sets of similarity search and deep neural network training."}}
other: {"actor":{"display_login":"jtarango"}}