The paper provides less detail on a second hardware effort, known as the DeNovo project. DeNovo "rethinks concurrent hardware as a co-designed component of our disciplined programming strategy, both for enforcing the discipline and for exploiting it for simpler and more efficient hardware."
The DeNovo design uses a virtual instruction set architecture, probably implementing type instructions and an integrated runtime environment. "DeNovo seeks a fundamental rethinking of concurrent hardware, given the assumption that most future software will be disciplined for better dependability," the paper said.
The group also sketched out some of its planned software projects. They include work on "a general-purpose disciplined shared memory language that builds upon modern object-oriented languages with strong safety properties, providing the programmer with all the familiar ease-of-use facilities of modern sequential languages in conjunction with disciplined parallelism."
The group also hopes to create techniques and tools to let domain experts design their own domain-specific environments. Such frameworks could optimize use of parallelism in specific fields.
A planned compiler will "support explicitly parallel deterministic languages, including
domain-specific languages." The group will also work on runtime engines that can virtualize programs across a wide range of heterogeneous processor environments.
Many of the projects are based on work by researchers at Illinois and elsewhere. The paper cites more than 100 published works in the field.
Twenty Illinois researchers authored the paper including the lab's co-founder Marc Snir, a former IBM researcher manager who helped design some of Big Blue's supercomputers and Wen-mei Hwu, a widely published researcher in multicore architectures.
The parallel computing lab at Illinois includes about 16 faculty and 25 students. The lab gets $2 million in funding a year for five years from Microsoft and Intel plus additional funds from the university.
That's enough to create proof-of-concept designs, said Snir. The group should be able to report progress on some of its milestones within two years, he added.
Despite years of work in parallel programming, researchers have not been able to find a model easy enough for use by mainstream programmers. Nevertheless, the Illinois paper sets an optimistic tone for its ambitious goals.
"Commonly used programming models are prone to subtle, hard to reproduce bugs, and parallel programs are notoriously hard to test due to data races, non-deterministic interleavings, and complex memory models," the paper notes in its introduction.
Nevertheless it concludes that "our work is driven by a foreseeable future where all client applications will be parallel, and the primary consumer feature that will drive the economics of future client software development will be the quality of the human interaction."
The researchers describe a vision where significant amounts of computing will continue to be handled on end user systems. Future massively multicore processors using new parallel methods will be able to run applications that enable virtual environments, remote immersive environments and natural language processing, according to the paper.