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-- OVERVIEW -- PREREQUISITES To build and use Piccolo, you will need a minimum of the following: * CMake (> 2.6) * OpenMPI * Python (2.*) * gcc/g++ (> 4) * protocol buffers If available, the following libraries will be used: * Python development headers; SWIG * TCMalloc * google-perftools In addition to these, Piccolo comes with several support libraries which are compiled as part of the build process; these are: * google-flags * google-logging On debian/ubuntu, the required libraries can be acquired by running: sudo apt-get install\ build-essential\ cmake\ g++\ libboost-dev\ libboost-python-dev\ libboost-thread-dev\ liblzo2-dev\ libnuma-dev\ libopenmpi-dev\ libprotobuf-dev \ libcr-dev\ libibverbs-dev\ openmpi-bin\ protobuf-compiler\ the optional libraries can be install via: sudo apt-get install libgoogle-perftools-dev python-dev swig -- BUILDING To build, simply run 'make' from the toplevel piccolo directory. After building output should be available in the build/ directory. Specifically, a successful build should generate an executable for each example case: build/ accelpagerank bipartmatch bipartmatch-trigger faceclass k-means matmul pagerank shortest-path shortest-path-trigger test-tables test-tables2 wordcount -- RUNNING To execute a Piccolo program, you will need to modify conf/mpi-cluster to point to the set of machines Piccolo will be executed on - for example, a file might look like: localhost slots=1 a slots=4 b slots=4 c slots=4 Which allows for running up to 12 workers (+ 1 master process). In addition to the MPI configuration, LD_LIBRARY_PATH must be set to allow the Piccolo .so files to be located; this can be done via: You can run an example via: LD_LIBRARY_PATH=build/ \ build/k-means \ --num_points=10000 \ --num_clusters=100 \ --workers=12 \ --hostfile=conf/mpi-cluster This will create and test a simple k-means clustering experiment using the workers specified. -- DEVELOPMENT For more information on how to create your own programs, check out the API documentation.
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