Gorilla is a methodology for generating FPGA-based solutions especially well suited for data parallel applications with fine grain irregularity. Irregularity simultaneously destroys performance and increases power consumption on many data parallel processors such as General Purpose Graphical Processor Units (GPGPUs). Gorilla achieves high performance and low power through the use of FPGA-tailored paralleliza-tion techniques and application-specific hardwired accelerators, processing engines, and communication mechanisms. Automatic compilation from a stylized C language and templates that define the hardware structure coupled with the intrinsic flexibility of FPGAs provide high performance, low power, and programmability. Gorilla's capabilities are demonstrated through the generation of a family of core-router network processors processing up to 100Gbps (200MPPS for 64B packets) supporting any mix of IPv4, IPv6), and Multi-Protocol Label Switching (MPLS) packets on a single FPGA with off-chip IP lookup tables. A 40Gbps version of that network processor was run with an embedded test rig on a Xilinx Virtex-6 FPGA, verifying for performance and correctness. Its measured power consumption is comparable to full custom, commercial network processors. In addition, it is demonstrated how Gorilla can be used to generate merged virtual routers, saving FPGA resources.
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