HPCwire: Compilers and More: Parallel Programming Made Easy?

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September 02, 2008

Compilers and More: Parallel Programming Made Easy?

by Michael Wolfe, Compiler Engineer, The Portland Group, Inc.

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Look at all the current research projects aimed at exactly that: making parallel programming easy!

The NESL language aims to "make parallel programming easy and portable." More precisely, its goal is to allow programmers "to write parallel code as concisely and clearly as sequential code, while achieving close to peak performance."

Microsoft's Parallel Computing Platform team aims to provide a runtime that provides support for parallelism, models, libraries and tools that "make it easy for developers to construct correct, efficient, maintainable and scalable parallel programs."

The CxC (C by C) language has one-sided communication operations, "which makes parallel programming easy and efficient."

My alma mater, the University of Illinois, has a new Universal Parallel Computing Research Center, whose goal is simply "Making parallel programming easy." Marc Snir, the Computer Science Department head, said the goal for this effort is to "make 'parallel programming' synonymous with 'programming'."

The Parallel Computing Lab at the University of California at Berkeley has adopted the goal to "make it easy to write correct programs that run efficiently on manycore systems, and which scale as the number of cores doubles every two years."

Intel's Threaded Building Blocks (TBB) extends C++ for parallelism in an easy to use and efficient manner.

Tim Mattson (Intel) points out that in "our quest to find that perfect language to make parallel programming easy," we have come up with an alarming array of parallel programming choices: MPI, OpenMP, Ct, HPF, TBB, Erlang, Shmem, Portals, ZPL, BSP, CHARM++, Cilk, Co-array Fortran, PVM, Pthreads, Windows threads, Tstreams, GA, Java, UPC, Titanium, Parlog, NESL, Split-C, and on and on.

Tim and I are colleagues on the OpenMP Language committee, which recently finalized the OpenMP 3.0 standard. OpenMP's mission is to define a "portable, scalable model that gives shared-memory parallel programmers a simple and flexible interface for developing parallel applications for platforms ranging from the desktop to the supercomputer." Is simple even easier than easy?

Every time I see someone claiming they've come up with a method to make parallel programming easy, I can't take them seriously. First, "making parallel programming easy" must be harder than "making programming easy," and I don't think we've reached that first milestone yet. Yes, I can (and do) knock off quick programs to search or compute something simple, but then I can knock off a quick project to build a bridge over the seasonal stream in our backyard, too. I wouldn't trust that bridge to freeway traffic, and I wouldn't trust that quick program to solve anyone else's problem, either.

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