The two companies are expected to launch a joint research initiative to tackle programming for multicore processors

Microsoft and Intel are expected to launch a joint research initiative on Tuesday to tackle programming for multicore processors.

Although the two PC industry giants have yet to announce the research venture at the time of writing, the Wall Street Journal reports that the venture will focus on multicore programming and that the bulk of the work will be done at the University of California at Berkeley.

The need for more research stems from the emergence of processors with two or more processing units, or cores, which have now become mainstream. With multiple cores, chip designers can boost a machine's processing muscle in a more energy-efficient way than by increasing the processor's clock speed.

But multicore technology poses a significant challenge to both hardware and software providers. Without writing programs to be optimised for multicore processors, applications will not benefit from the added chip power, or could run slower than previous chips.

Both Microsoft and Intel — as well other IT companies — have made programming tools for multicore processing a high priority in terms of product development and research.

The amount of funding for the research, which several universities bid on, will be $2m (£1m) annually for five years, according to the Wall Street Journal. A report from EE Times said about 14 faculty members at the University of California at Berkeley lab started work on the project in late January. The research will focus on creating development frameworks that make it easier for programmers to parse out computing jobs so that they can be done in parallel by processors with several cores, according to the report.

Essentially, the lab is aiming to define a way to compose parallel programs based on flexible sets of standard modules in a way similar to how serial programs are written today. The challenge in the parallel world is finding a dynamic and flexible approach to schedule parallel tasks from these modules across available hardware in complex heterogeneous multicore CPUs.

The group believes developers could create a set of perhaps a dozen frameworks that understand the intricacies of the hardware. The frameworks could be used to write modules that handle specific tasks such as solving a matrix. New run-time environments could dynamically schedule the modules across available cores of various types.

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