{"action":"reopened","issue":{"url":"https://api.github.com/repos/m-a-d-n-e-s-s/madness/issues/24","labels_url":"https://api.github.com/repos/m-a-d-n-e-s-s/madness/issues/24/labels{/name}","comments_url":"https://api.github.com/repos/m-a-d-n-e-s-s/madness/issues/24/comments","events_url":"https://api.github.com/repos/m-a-d-n-e-s-s/madness/issues/24/events","html_url":"https://github.com/m-a-d-n-e-s-s/madness/issues/24","id":39048667,"number":24,"title":"Segmentation fault in mTxmq when running testsuite","user":{"login":"richford","id":7978135,"avatar_url":"https://avatars.githubusercontent.com/u/7978135?v=3","gravatar_id":"","url":"https://api.github.com/users/richford","html_url":"https://github.com/richford","followers_url":"https://api.github.com/users/richford/followers","following_url":"https://api.github.com/users/richford/following{/other_user}","gists_url":"https://api.github.com/users/richford/gists{/gist_id}","starred_url":"https://api.github.com/users/richford/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/richford/subscriptions","organizations_url":"https://api.github.com/users/richford/orgs","repos_url":"https://api.github.com/users/richford/repos","events_url":"https://api.github.com/users/richford/events{/privacy}","received_events_url":"https://api.github.com/users/richford/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":{"login":"richford","id":7978135,"avatar_url":"https://avatars.githubusercontent.com/u/7978135?v=3","gravatar_id":"","url":"https://api.github.com/users/richford","html_url":"https://github.com/richford","followers_url":"https://api.github.com/users/richford/followers","following_url":"https://api.github.com/users/richford/following{/other_user}","gists_url":"https://api.github.com/users/richford/gists{/gist_id}","starred_url":"https://api.github.com/users/richford/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/richford/subscriptions","organizations_url":"https://api.github.com/users/richford/orgs","repos_url":"https://api.github.com/users/richford/repos","events_url":"https://api.github.com/users/richford/events{/privacy}","received_events_url":"https://api.github.com/users/richford/received_events","type":"User","site_admin":false},"milestone":{"url":"https://api.github.com/repos/m-a-d-n-e-s-s/madness/milestones/1","html_url":"https://github.com/m-a-d-n-e-s-s/madness/milestones/Release%20Candidate%200.10","labels_url":"https://api.github.com/repos/m-a-d-n-e-s-s/madness/milestones/1/labels","id":758818,"number":1,"title":"Release Candidate 0.10","description":"The release will include:\r\n- Basic MADNESS functionality cleaned up\r\n- Documentation\r\n- Reorg, cleanup, documentation, build/install\r\n- Test performance and correctness and reproducibility and regression testing … automated script for someone to run … leverage CI stuff\r\n- Linux/OSX laptop, BG, Titan … configure out of box with near zero options, George will test Cray\r\n- Distributed matrix and parallel eigenstuff\r\n","creator":{"login":"justusc","id":5115941,"avatar_url":"https://avatars.githubusercontent.com/u/5115941?v=3","gravatar_id":"","url":"https://api.github.com/users/justusc","html_url":"https://github.com/justusc","followers_url":"https://api.github.com/users/justusc/followers","following_url":"https://api.github.com/users/justusc/following{/other_user}","gists_url":"https://api.github.com/users/justusc/gists{/gist_id}","starred_url":"https://api.github.com/users/justusc/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/justusc/subscriptions","organizations_url":"https://api.github.com/users/justusc/orgs","repos_url":"https://api.github.com/users/justusc/repos","events_url":"https://api.github.com/users/justusc/events{/privacy}","received_events_url":"https://api.github.com/users/justusc/received_events","type":"User","site_admin":false},"open_issues":9,"closed_issues":28,"state":"open","created_at":"2014-08-19T15:13:16Z","updated_at":"2015-04-03T20:52:45Z","due_on":"2014-10-24T07:00:00Z","closed_at":null},"comments":5,"created_at":"2014-07-30T00:03:00Z","updated_at":"2015-04-03T20:52:45Z","closed_at":null,"body":"Running testsuite produces a segmentation fault in mTxmq when Testing 1-D separated operators.  @wsttiger, mTxmq is yours right?  Can anyone else using LLVM 6.0 reproduce this?\r\n\r\n`(gdb) run` terminates with:\r\n```\r\nTest separated operators - type = std::complex<double> , ndim = 1 \r\n\r\ntimer:              project     0.00s     0.00s\r\n         f norm is 1.00000000e+00\r\n     f total error 4.27882902e-14\r\n[New Thread 0x170b of process 92944]\r\n[New Thread 0x1803 of process 92944]\r\n[New Thread 0x1903 of process 92944]\r\n\r\nProgram received signal SIGSEGV, Segmentation fault.\r\n0x000000010090b946 in madness::mTxmq<std::__1::complex<double>, double, std::__1::complex<double> > (dimi=4330568192, dimj=20, dimk=0, c=<optimized out>, a=<optimized out>, b=0x1021f3ae0) at mtxmq.cc:1383\r\n1383\t            __asm__ volatile\r\n```\r\n\r\n`(gdb) where` returns:\r\n```\r\n#0  0x000000010090b946 in madness::mTxmq<std::__1::complex<double>, double, std::__1::complex<double> > (dimi=4330568192, dimj=20, dimk=0, c=<optimized out>, a=<optimized out>, b=0x1021f3ae0) at mtxmq.cc:1383\r\n#1  0x00000001000f5739 in madness::Tensor<madness::TensorResultType<std::__1::complex<double>, double>::type>& madness::fast_transform<std::__1::complex<double>, double>(madness::Tensor<std::__1::complex<double> > const&, madness::Tensor<double> const&, madness::Tensor<madness::TensorResultType<std::__1::complex<double>, double>::type>&, madness::Tensor<madness::TensorResultType<std::__1::complex<double>, double>::type>&) ()\r\n#2  0x00000001000f4f45 in madness::Tensor<madness::TensorResultType<std::__1::complex<double>, double>::type> madness::transform<std::__1::complex<double>, double>(madness::Tensor<std::__1::complex<double> > const&, madness::Tensor<double> const&) ()\r\n#3  0x000000010010d8a3 in madness::Convolution1D<std::__1::complex<double> >::nonstandard(int, long long) const ()\r\n#4  0x000000010010cd41 in madness::SeparatedConvolution<std::__1::complex<double>, 1ul>::getmuop(int, int, madness::Key<1ul> const&) const ()\r\n#5  0x000000010010528a in madness::SeparatedConvolution<std::__1::complex<double>, 1ul>::getop_ns(int, madness::Key<1ul> const&) const ()\r\n#6  0x00000001000fe746 in double madness::FunctionImpl<std::__1::complex<double>, 1ul>::do_apply_directed_screening<madness::SeparatedConvolution<std::__1::complex<double>, 1ul> const, std::__1::complex<double> >(madness::SeparatedConvolution<std::__1::complex<double>, 1ul> const*, madness::Key<1ul> const&, madness::GenTensor<std::__1::complex<double> > const&, bool const&) ()\r\n#7  0x00000001000fdc00 in madness::FunctionImpl<std::__1::complex<double>, 1ul>::recursive_apply_op2<madness::SeparatedConvolution<std::__1::complex<double>, 1ul> const>::operator()(madness::Key<1ul> const&) const ()\r\n#8  0x00000001000fd533 in madness::Void madness::FunctionImpl<std::__1::complex<double>, 1ul>::traverse_tree<madness::FunctionImpl<std::__1::complex<double>, 1ul>::recursive_apply_op2<madness::SeparatedConvolution<std::__1::complex<double>, 1ul> const>, madness::noop<std::__1::complex<double>, 1ul> >(madness::FunctionImpl<std::__1::complex<double>, 1ul>::recursive_apply_op2<madness::SeparatedConvolution<std::__1::complex<double>, 1ul> const> const&, madness::noop<std::__1::complex<double>, 1ul> const&, madness::Key<1ul> const&) const ()\r\n#9  0x0000000100115eb7 in madness::TaskFn<madness::detail::MemFuncWrapper<madness::FunctionImpl<std::__1::complex<double>, 1ul> const*, madness::Void (madness::FunctionImpl<std::__1::complex<double>, 1ul>::*)(madness::FunctionImpl<std::__1::complex<double>, 1ul>::recursive_apply_op2<madness::SeparatedConvolution<std::__1::complex<double>, 1ul> const> const&, madness::noop<std::__1::complex<double>, 1ul> const&, madness::Key<1ul> const&) const, madness::Void>, madness::Future<madness::FunctionImpl<std::__1::complex<double>, 1ul>::recursive_apply_op2<madness::SeparatedConvolution<std::__1::complex<double>, 1ul> const> >, madness::noop<std::__1::complex<double>, 1ul>, madness::Key<1ul>, void, void, void, void, void, void>::run(madness::TaskThreadEnv const&) ()\r\n#10 0x0000000100058119 in madness::PoolTaskInterface::run_multi_threaded() ()\r\n#11 0x0000000100057d01 in madness::ThreadPool::run_task() ()\r\n#12 0x000000010020a6c9 in madness::WorldTaskQueue::fence() ()\r\n#13 0x0000000100924dde in madness::WorldGopInterface::fence (this=0x101f077a0) at worldgop.cc:67\r\n#14 0x00000001000fcde2 in void madness::FunctionImpl<std::__1::complex<double>, 1ul>::recursive_apply<madness::SeparatedConvolution<std::__1::complex<double>, 1ul> const>(madness::SeparatedConvolution<std::__1::complex<double>, 1ul> const&, madness::FunctionImpl<std::__1::complex<double>, 1ul> const*, madness::FunctionImpl<std::__1::complex<double>, 1ul>*, bool) ()\r\n#15 0x00000001000fbb44 in madness::Function<madness::TensorResultType<madness::SeparatedConvolution<std::__1::complex<double>, 1ul>::opT, std::__1::complex<double> >::type, 1ul> madness::apply_only<madness::SeparatedConvolution<std::__1::complex<double>, 1ul>, std::__1::complex<double>, 1ul>(madness::SeparatedConvolution<std::__1::complex<double>, 1ul> const&, madness::Function<std::__1::complex<double>, 1ul> const&, bool) ()\r\n#16 0x00000001000fa924 in madness::Function<madness::TensorResultType<madness::SeparatedConvolution<std::__1::complex<double>, 1ul>::opT, std::__1::complex<double> >::type, 1ul> madness::apply<madness::SeparatedConvolution<std::__1::complex<double>, 1ul>, std::__1::complex<double>, 1ul>(madness::SeparatedConvolution<std::__1::complex<double>, 1ul> const&, madness::Function<std::__1::complex<double>, 1ul> const&, bool) ()\r\n#17 0x000000010001c015 in int test_op<std::__1::complex<double>, 1ul>(madness::World&) ()\r\n#18 0x00000001000041ef in main (argc=1, argv=0x7fff5fbff910) at testsuite.cc:1316\r\n```\r\n\r\n`mpicxx -v` returns\r\n```\r\nmpicxx for MPICH version 3.1.2\r\nApple LLVM version 6.0 (clang-600.0.41.2) (based on LLVM 3.5svn)\r\nTarget: x86_64-apple-darwin13.3.0\r\nThread model: posix\r\n```\r\n\r\nAnd I'm on a Macbook Pro with 8 GB 1600 MHz DDR3 memory and an Intel Core i5 processor."}}