A Scalable Parallel Architecture with FPGA-Based Network Processor for Scientific Computing

This thesis discuss the design and the implementation of an FPGA-Based Network Processor for scientific computing, like Lattice Quantum ChromoDinamycs (LQCD) and fluid-dynamics applications based on Lattice Boltzmann Methods (LBM). State-of-the-art programs in this (and other similar) applications have a large degree of available parallelism, that can be easily exploited on massively parallel systems, provided the underlying communication network has not only high-bandwidth but also low-latency. I have designed in details, built and tested in hardware, firmware and software an implementation of a Network Processor, tailored for the most recent families of multi-core processors. The implementation has been developed on an FPGA device to easily interface the logic of NWP with the CPU I/O sub-system. In this work I have assessed several ways to move data between the main memory of the CPU and the I/O sub-system to exploit high data throughput and low latency, enabling the use of “Programmed Input Output” (PIO), “Direct Memory Access” (DMA) and “Write Combining” memory-settings. On the software side, I developed and test a device driver for the Linux operating system to access the NWP device, as well as a system library to efficiently access the network device from user-applications. This thesis demonstrates the feasibility of a network infrastructure that saturates the maximum bandwidth of the I/O sub-systems available on recent CPUs, and reduces communication latencies to values very close to those needed by the processor to move data across the chip boundary.