Increasing demand for both greater parallelism and faster clocks dictate that future generation architectures will need to decentralize their resources and eliminate primitives that require single cycle global communication. A Raw microprocessor distributes all of its resources, including instruction streams, register files, memory ports, and ALUs, over a pipelined two-dimensional mesh interconnect, and exposes them fully to the compiler. Because communication in Raw machines is distributed, compiling for instruction-level parallelism (ILP) requires both spatial instruction partitioning as well as traditional temporal instruction scheduling. In addition, the compiler must explicitly manage all communication through the interconnect, including the global synchronization required at branch points. This paper describes RAWCC, the compiler we have developed for compiling general-purpose sequential programs to the distributed Raw architecture. We present performance results that demonstrate that although Raw machines provide no mechanisms for global communication the Raw compiler can schedule to achieve speedups that scale with the number of available functional units.

The RAW benchmark suite consists of twelve programs designed to facilitate comparing, validating, and improving reconfigurable computing systems. These benchmarks run the gamut of algorithms found in general purpose computing, including sorting, matrix operations, and graph algorithms. The suite includes an architecture-independent compilation framework, Raw Computation Structures (RawCS), to express each algorithm's dependencies and to support automatic synthesis, partitioning, and mapping to a reconfigurable computer. Within this framework, each benchmark is portably designed in both C and Behavioral Verilog and scalably parameterized to consume a range of hardware resource capacities. To establish initial benchmark ratings, we have targeted a commercial logic emulation system based on virtual wires technology to automatically generate designs up to millions of gates (14 to 379 FPGAs). Because the virtual wires techniques abstract away machine-level details like FPGA capacity and interconnect, our hardware target for this system is an abstract reconfigurable logic fabric with memory-mapped host I/O. We report initial speeds in the range of 2X to 1800X faster than a 2.82 SPECint95 SparcStation 20 and encourage others in the field to run these benchmarks on other systems to provide a standard comparison.