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 multi-core 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.
The new approach would replace the global schedulers used in today's serial software. The frameworks would replace today's parallel libraries which are not always well suited to the specifics of a given parallel application and cannot be easily mixed and matched as needed.
The Berkeley effort has set its sights on a long term horizon beyond the 8-16 core processors likely to hit the market in mainstream CPUs in the next two to five years. Instead it will focus on problems programming chips with dozens of cores.
Researchers believe that over the next five years or so chip makers will use a fairly diverse set of cores. However, as time goes on those cores may become increasingly similar to make it easier both to verify the silicon and program the hardware.
Researchers at Stanford are continuing to work in this area despite not getting the Intel/Microsoft funding. Their current focus is on combining two projects.
One project uses transactional memory technology to find ways to handle dynamic scheduling. Another uses a novel language called Sequoia aimed at data-intensive applications such as digital media processing.
Researchers at the University of Illinois, meanwhile, have explored ways to extract parallelism from today's serial code. They have also worked on compilers and programming models for next-generation graphics chips as well as the Intel Itanium processor.