ParaFPGA 2011 : high performance computing with multiple FPGAs : design, methodology and applications

ParaFPGA 2011 marks the third mini-symposium devoted to the methodology, design and implementation of parallel applications using FPGAs. The focus of the contributions is mainly on organizing parallel applications in multiple FPGAs. This includes experiences from building a supercomputer with FPGAs, automatic and dedicated balancing of different tasks on heterogeneous FPGA constellations and designing optimal interconnects between collaborating FPGAs

8x8 Reconfigurable quantum photonic processor based on silicon nitride waveguides

The development of large-scale optical quantum information processing circuits ground on the stability and reconfigurability enabled by integrated photonics. We demonstrate a reconfigurable 8x8 integrated linear optical network based on silicon nitride waveguides for quantum information processing. Our processor implements a novel optical architecture enabling any arbitrary linear transformation and constitutes the largest programmable circuit reported so far on this platform. We validate a variety of photonic quantum information processing primitives, in the form of Hong-Ou-Mandel interference, bosonic coalescence/anticoalescence and high-dimensional single-photon quantum gates. We achieve fidelities that clearly demonstrate the promising future for large-scale photonic quantum information processing using low-loss silicon nitride.Comment: Added supplementary materials, extended introduction, new figures, results unchange

Pixie: A heterogeneous Virtual Coarse-Grained Reconfigurable Array for high performance image processing applications

Coarse-Grained Reconfigurable Arrays (CGRAs) enable ease of programmability and result in low development costs. They enable the ease of use specifically in reconfigurable computing applications. The smaller cost of compilation and reduced reconfiguration overhead enables them to become attractive platforms for accelerating high-performance computing applications such as image processing. The CGRAs are ASICs and therefore, expensive to produce. However, Field Programmable Gate Arrays (FPGAs) are relatively cheaper for low volume products but they are not so easily programmable. We combine best of both worlds by implementing a Virtual Coarse-Grained Reconfigurable Array (VCGRA) on FPGA. VCGRAs are a trade off between FPGA with large routing overheads and ASICs. In this perspective we present a novel heterogeneous Virtual Coarse-Grained Reconfigurable Array (VCGRA) called "Pixie" which is suitable for implementing high performance image processing applications. The proposed VCGRA contains generic processing elements and virtual channels that are described using the Hardware Description Language VHDL. Both elements have been optimized by using the parameterized configuration tool flow and result in a resource reduction of 24% for each processing elements and 82% for each virtual channels respectively.Comment: Presented at 3rd International Workshop on Overlay Architectures for FPGAs (OLAF 2017) arXiv:1704.0880