Using Memchecker ================ The Memchecker functionality in Open MPI provides MPI semantic checking for your application (as well as internals of Open MPI), with the help of memory checking tools such as the ``memcheck`` component of `the Valgrind suite `_. ///////////////////////////////////////////////////////////////////////// Types of Errors Detected by Memchecker -------------------------------------- Open MPI's Memchecker is based on the ``memcheck`` tool included with Valgrind, so it takes all the advantages from it. Firstly, it checks all reads and writes of memory, and intercepts calls to ``malloc(3)``/``free(3)`` and C++'s ``new``/``delete`` operators. Most importantly, Memchecker is able to detect the user buffer errors in both non-blocking and one-sided communications, e.g. reading or writing to buffers of active non-blocking receive operations and writing to buffers of active non-blocking send operations. Here are some example problems that Memchecker can detect: Accessing buffer under control of non-blocking communication: .. code-block:: c int buf; MPI_Irecv(&buf, 1, MPI_INT, 1, 0, MPI_COMM_WORLD, &req); // The following line will produce a memchecker warning buf = 4711; MPI_Wait (&req, &status); Wrong input parameters, e.g., wrong-sized send buffers: .. code-block:: c char *send_buffer; send_buffer = malloc(5); memset(send_buffer, 0, 5); // The following line will produce a memchecker warning MPI_Send(send_buffer, 10, MPI_CHAR, 1, 0, MPI_COMM_WORLD); Accessing a window in a one-sided communication: .. code-block:: c MPI_Get(A, 10, MPI_INT, 1, 0, 1, MPI_INT, win); A[0] = 4711; MPI_Win_fence(0, win); Uninitialized input buffers: .. code-block:: c char *buffer; buffer = malloc(10); // The following line will produce a memchecker warning MPI_Send(buffer, 10, MPI_INT, 1, 0, MPI_COMM_WORLD); Usage of the uninitialized ``MPI_Status`` field in ``MPI_ERROR`` structure: (the MPI-1 standard defines the ``MPI ERROR`` field to be undefined for single-completion calls such as :ref:`MPI_Wait(3) ` or :ref:`MPI_Test(3) `, see MPI-1 p. 22): .. code-block:: c MPI_Wait(&request, &status); // The following line will produce a memchecker warning if (status.MPI_ERROR != MPI_SUCCESS) return ERROR; ///////////////////////////////////////////////////////////////////////// Building Open MPI with Memchecker Support ----------------------------------------- To use Memchecker, you need Valgrind 3.2.0 or later, and have an Open MPI that was configured with the ``--enable-memchecker`` and ``--enable-debug`` flags. .. note:: The Memchecker functionality is off by default, because it incurs a performance penalty. When ``--enable-memchecker`` is specified, ``configure`` will check for a recent-enable valgrind distribution. If found, Open MPI will build Memchecker support. For example: .. code-block:: sh shell$ ./configure --prefix=/path/to/openmpi --enable-debug \ --enable-memchecker --with-valgrind=/path/to/valgrind You can check that Open MPI was built with Memchecker support by using the :ref:`ompi_info(1) ` command. .. code-block:: sh # The exact version numbers shown may be different for your Open # MPI installation shell$ ompi_info | grep memchecker MCA memchecker: valgrind (MCA v1.0, API v1.0, Component v1.3) If you do not see the "MCA memchecker: valgrind" line, you probably did not configure and install Open MPI correctly. ///////////////////////////////////////////////////////////////////////// Running an Open MPI Application with Memchecker ----------------------------------------------- After Open MPI was built and installed with Memchecker support, simply run your application with Valgrind, e.g.: .. code-block:: sh shell$ mpirun -n 2 valgrind ./my_app If you enabled Memchecker, but you don't want to check the application at this time, then just run your application as usual. E.g.: .. code-block:: sh shell$ mpirun -n 2 ./my_app ///////////////////////////////////////////////////////////////////////// Application Performance Impacts Using Memchecker ------------------------------------------------ The configure option ``--enable-memchecker`` (together with ``--enable-debug``) *does* cause performance degradation, even if not running under Valgrind. The following explains the mechanism and may help in making the decision whether to provide a cluster-wide installation with ``--enable-memchecker``. There are two cases: #. If run without Valgrind, the Valgrind ClientRequests (assembler instructions added to the normal execution path for checking) do not affect overall MPI performance. Valgrind ClientRequests are explained in detail `in Valgrind's documentation `_. In the case of x86-64, ClientRequests boil down to the following four rotate-left (ROL) and one xchange (XCHG) assembler instructions from ``valgrind.h``: .. code-block:: c #define __SPECIAL_INSTRUCTION_PREAMBLE \ "rolq \$3, %%rdi; rolq \$13, %%rdi\\n\\t" \ "rolq \$61, %%rdi; rolq \$51, %%rdi\\n\\t" and .. We do not make the code block below as "c" because the Sphinx C syntax highlighter fails to parse it as C and emits a warning. So we might as well just leave it as a plan verbatim block (i.e., not syntax highlighted). .. code-block:: __asm__ volatile(__SPECIAL_INSTRUCTION_PREAMBLE \ /* %RDX = client_request ( %RAX ) */ \ "xchgq %%rbx,%%rbx" \ : "=d" (_zzq_result) \ : "a" (& _zzq_args``0``), "0" (_zzq_default) \ : "cc", "memory" \ ); for every single ClientRequest. In the case of not running Valgrind, these ClientRequest instructions do not change the arithmetic outcome (rotating a 64-bit register left by 128-Bits, exchanging a register with itself), except for the carry flag. The first request is checking whether we're running under Valgrind. In case we're not running under Valgrind subsequent checks (a.k.a. ClientRequests) are not done. #. If the application is run under Valgrind, performance is naturally reduced due to the Valgrind JIT and the checking tool employed. For costs and overheads of Valgrind's Memcheck tool on the SPEC 2000 Benchmark, please see the excellent paper `Valgrind: A Framework for Heavyweight Dynamic Binary Instrumentation `_. For an evaluation of various internal implementation alternatives of Shadow Memory, please see `Building Workload Characterization Tools with Valgrind `_.