Project Summary Desktop processor architectures have crossed a critical threshold. Manufactures have given up attempting to extract ever more performance from a single core and instead have turned to multi-core designs. While straightforward approaches to the architecture of multi-core processors are sufficient for small designs (2-4 cores), little is really known how to build, program, or manage systems of 64 to 1024 processors. Unfortunately, the computer architecture community lacks the

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... infrastructure tools required to carry out this research. While simulation has been adequate for single-processor research, significant use of simplified modeling and statistical sampling is required to work in the 2-16 processing core space. Invention is required for architecture research at the level of 64-1024 cores. Fortunately, Moore's law has not only enabled these dense multi-core chips, it has also enabled extremely dense FPGAs. Today, for a few hundred dollars, undergraduates can work with an FPGA prototype board with almost as many gates as a Pentium. Given the right support, the research community can capitalize on this opportunity too. Today, one to two dozen cores can be programmed into a single FPGA. With multiple FPGAs on a board and multiple boards in a system, large complex architectures can be explored. To make this happen, however, requires a significant amount of infrastructure in hardware, software, and what we call "gateware", the register-transfer level models that fill the FGPAs. While it is possible for each research group to create these boards, design the gateware, and create this infrastructure in isolation, significant benefits can be had by pooling our collective resources. Such a system would not just invigorate multiprocessors research in the architecture community. Since processors cores can run at 100 to 200 MHz, a large scale multiprocessor would be fast enough to run operating systems and large programs at speeds sufficient to support software research. Moreover, there is a new generation of FPGAs every 18 months that is roughly twice as fast and with capacity for twice as many cores, so future multiboard FPGA systems are even more attractive. Hence, we believe such a system would accelerate research across all the fields that touch multiple processors: operating systems, compilers, debuggers, programming languages, scientific libraries, and so on. Thus the acronymn RAMP, for Research Accelerator for Multiple Processors. This project intends to foster just such a community endeavor. By leveraging the work that each of us was going to do anyway in isolation, we can create a shared infrastructure for architecture research. Furthermore, by pooling our resources in hardware design we can reduce the risk each of us undertakes by designing hardware prototypes ourselves. Finally, by creating shared and supported baseline platforms for multi-core architectures we can jump start the required architecture and critical software research that the field needs. Intellectual Merit The intellectual merit of this project is embodied in the following contribution. First, we intend to create a set of RTL and software design standards that facilitate easy adaptability and integration of hardware and software components in the multi-core architecture. Second, we intend to use these design standards to create a baseline architecture of 1024+ nodes. Third, we will investigate architectures for fast emulation of large scale multiprocessors. For example, what type of memory controller and caches will speedup emulation of 1024 processors. Fourth, we will create systems to observe the MPP behavior without disturbing the computation. This design will be created, distributed for free on the Internet, and supported through full-time staff. Broader Impact The broader impact goal of this project is nothing less than the transformation of the parallel computing community in computer science from a simulation-driven to a prototype-driven discipline. RAMP will enable the rapid iteration across interfaces of the many fields of multiple processors, thereby more quickly ramping up a parallel foundation for large-scale computer systems research in the 21st century.