MatlabMPI

MatlabMPI. In many projects the true costs of high performance computing are currently dominated by software. Addressing these costs may require shifting to higher level languages such as Matlab. MatlabMPI is a Matlab implementation of the Message Passing Interface (MPI) standard and allows any Matlab program to exploit multiple processors. MatlabMPI currently implements the basic six functions that are the core of the MPI point-to-point communications standard. The key technical innovation of MatlabMPI is that it implements the widely used MPI “look and feel” on top of standard Matlab file I/O, resulting in an extremely compact (∼350 lines of code) and “pure” implementation which runs anywhere Matlab runs, and on any heterogeneous combination of computers. The performance has been tested on both shared and distributed memory parallel computers (e.g. Sun, SGI, HP, IBM, Linux, MacOSX and Windows). MatlabMPI can match the bandwidth of C based MPI at large message sizes. A test image filtering application using MatlabMPI achieved a speedup of ∼300 using 304 CPUs and ∼15% of the theoretical peak (450 Gigaflops) on an IBM SP2 at the Maui High Performance Computing Center. In addition, this entire parallel benchmark application was implemented in 70 software-lines-of-code, illustrating the high productivity of this approach. MatlabMPI is available for download on the web (www.ll.mit.edu/MatlabMPI).


References in zbMATH (referenced in 9 articles , 1 standard article )

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  1. Bhatt, H. P.; Khaliq, A. Q. M.: A compact fourth-order (L)-stable scheme for reaction-diffusion systems with nonsmooth data (2016)
  2. Islam, Syed M. S.; Davies, Rowan; Bennamoun, Mohammed; Mian, Ajmal S.: Efficient detection and recognition of 3D ears (2011) ioport
  3. Mercatoris, B. C. N.; Massart, T. J.: A coupled two-scale computational scheme for the failure of periodic quasi-brittle thin planar shells and its application to masonry (2011)
  4. Pacull, F.; Garbey, M.: A parallel immersed boundary method for blood-like suspension flow simulations (2010)
  5. Hudak, David E.; Ludban, Neil; Krishnamurthy, Ashok; Gadepally, Vijay; Samsi, Siddharth; Nehrbass, John: A computational science IDE for HPC systems: design and applications (2009)
  6. Sharma, Gaurav; Martin, Jos: MATLAB(^\circledR): A language for parallel computing (2009)
  7. Dalcín, Lisandro; Paz, Rodrigo; Storti, Mario; D’elía, Jorge: MPI for python: performance improvements and MPI-2 extensions (2008) ioport
  8. Lau, Henry Y. K.; Tsang, Wilburn W. P.: A parallel immune optimization algorithm for numeric function optimization (2008) ioport
  9. Kepner, Jeremy; Ahalt, Stan: MatlabMPI (2004)