Ct: channelling NeSL and SISAL in C++

I will discuss the design of Ct, an API for nested data parallel programming in C++. Ct uses meta-programming and functional language ideas to essentially embed a pure functional programming language in impure and unsafe languages, like C++. I will discuss the evolution of the design into functional programming ideas, how this was received in the corporate world, and how we plan to proliferate the technology in the next year.

Ct is a deterministic parallel programming model integrating the nested data parallelism ideas of Blelloch and bulk synchronous processing ideas of Valiant. That is, data races are not possible in Ct. Moreover, performance in Ct is relatively predictable. At its inception, Ct was conceived as a simple library implementation behind C++ template magic. However, performance issues quickly forced us to consider some form of compilation. Using template programming was highly undesirable for this purpose as it would have been difficult and overly specific to C++ idiosyncrasies. Moreover, once compilation for performance was considered, we began to consider a language semantics that would enable powerful optimizations like calculational fusion, synchronization barrier elimination, and so on. The end result of this deliberation is an API that exposes a value-oriented, purely functional vector processing language. Additional benefits of this approach are numerous, including the important ability to co-exist within legacy threading programming models (because of the data isolation inherent in the model). We will show how the model applies to a wide range of important (at least by cycle count) applications. Ct targets both shipping multi-core architectures from Intel as well as future announced architectures.

The corporate reception to this approach has (pleasantly) surprised us. In the desktop and high-performance computing space, where C, C++, Java, and Fortran are the only programming models people talk about, we have made serious inroads into advocating advanced programming language technologies. The desperate need for productive, scalable, and safe programming languages for multi-core architectures has provided an opening for functional, type-safe languages. We will discuss the struggles of multi-core manufacturers (i.e. Intel) and their software vendors that have created this opening.

For Intel, Ct heralds its first serious effort to champion a technology that borrows functional programming technologies from the research community. Though it is a compromise that accommodates the pure in the impure and safe in the unsafe, this is an important opportunity to demonstrate the power of functional programming to the unconverted. We plan to share the technology selectively with partners and collaborators, and will have a fully functional and parallelizing implementation by year's end. At CUFP, we will be prepared to discuss our long term plans in detail.