HPCwire: MATLAB's Journey to Parallel Computing

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November 15, 2007

MATLAB's Journey to Parallel Computing

by Michael Feldman, HPCwire Editor

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Propelled by its flagship MATLAB product, The MathWorks is one of the most important suppliers of software tools for the technical computing community. The MATLAB (MATrix LABoratory) language has become the preeminent interactive programming environment for scientists and engineers. Over a million customers are using it to develop technical computing applications around the world.

Recently, we got the opportunity to speak with The MathWorks co-founder and chief scientist Cleve Moler about the evolution of MATLAB and about how the language grew to include parallel programming support. The history of the MATLAB product spans over two decades.

In the early 1980s, Jack Little defined the business plan for the company, to be known as The MathWorks, while Moler was the brains behind MATLAB. Both Moler and Little, along with Steve Banger, developed the initial commercial product, MATLAB 1.0, which was launched in 1984, the same year The MathWorks was founded. Moler modestly refers to Little as the "heart and soul of the company," but it is MATLAB that has become the company's icon.

"I wrote MATLAB years ago, so I wouldn't have to go down to the computer center after dinner to pick up my output," said Moler. "It was important that MATLAB be interactive. That was more important to me than it was for it to be fast. I was worried about my time, not the computer's time."

But in the world of high performance technical computing, fast execution is also a big priority. When you start running applications that take weeks to complete on your PC, interactivity doesn't mean much. These users want to tap parallel computing and still have an interactive workflow for even their largest data sets.

Although MATLAB started out as a single-threaded, shared memory programming language for the PC, even in those early days people were experimenting with it as a platform for parallel computing. In the 1980s, a few engineers were starting to use the INMOS transputer as a math accelerator. Moler said a South African company wrote a set of library functions for the transputer, and these became add-ons to MATLAB. In the late 80s, Moler himself played around with MATLAB on the Intel HyperCube, an early implementation of a parallel computer. But in these cases, MATLAB was used as the front-end for the parallel computations on the parallel computer. The language environment did not run natively on these architectures.

For the next decade, that became a recurring theme that stood in the way of extending MATLAB into parallel computing. In 1995, Moler wrote "Why There Isn't a Parallel MATLAB," in which he described the three major obstacles at the time: the memory model, granularity, and the business situation.

The conflict between MATLAB's global memory model and the distributed model of most parallel systems meant that the large data matrices had to be sent back and forth between the host and the parallel computer. "It took far longer to distribute the data than it did to do the computation," wrote Moler at the time. "Any matrix that would fit into memory on the host was too small to make effective use of the parallel computer itself."

And on the shared memory machines of that era, it would have been difficult to implement the kind of multithreaded parallelism that would have made the design changes in the product worthwhile.

The other major problem was that early parallel computers were not built to be user-friendly. In the 1980s and 1990s, mainstream computing was still relying on Moore's law to drive performance increases with single-core, single processor systems. The multiprocessor systems of the day were the mainframes and supercomputers, and as Moler noted, the people who owned these system didn't buy any software; they developed it themselves. In most cases, these machines did not offer interactivity, which negates one of the main features of MATLAB.

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