Software defined FFT architecture for IEEE 802.11ac

The upcoming IEEE 802.11ac standard boosts the throughput of previous IEEE 802.11n by adding wider 80 MHz and 160 MHz channels with up to 8 antennas (versus 40 MHz channel and 4 antennas in 802.11n). This necessitates new 1-8 stream 256/512-point Fast Fourier Transform (FFT) / inverse FFT (IFFT) processing with 80/160 MSample/s throughput. Although there are abundant related work, they all fail to meet the requirements of IEEE 802.11ac FFT/IFFT on point size, throughput and multiple data streams at the same time. This paper proposes the first software defined FFT/IFFT architecture as a solution. By making use of a customised soft stream processor on FPGA, we show how a software defined FFT architecture can meet all the requirements of IEEE 802.11ac with low cost and high resource efficiency. When compared with dedicated Xilinx FFT core, our implementation exhibits only one third of the resources also up to three times of resource efficiency.

FPGA based Streaming Image Processing Processor (SIPPro) architecture to accelerate data intensive applications

Current data-intensive image processing applications push traditional embedded architectures to their limits. FPGA based hardware acceleration is a potential solution but the programmability gap and time consuming HDL design flow is significant. The proposed research approach to develop “FPGA based programmable hardware acceleration platform” that uses, large number of Streaming Image processing Processors (SIPPro) potentially addresses these issues. SIPPro is pipelined in-order soft-core processor architecture with specific optimisations for image processing applications. Each SIPPro core uses 1 DSP48, 2 Block RAMs and 370 slice-registers, making the processor as compact as possible whilst maintaining flexibility and programmability. It is area efficient, scalable and high performance softcore architecture capable of delivering 530 MIPS per core using Xilinx Zynq SoC (ZC7Z020-3). To evaluate the feasibility of the proposed architecture, a Traffic Sign Recognition (TSR) algorithm has been prototyped on a Zedboard with the color and morphology operations accelerated using multiple SIPPros. Simulation and experimental results demonstrate that the processing platform is able to achieve a speedup of 15 and 33 times for color filtering and morphology operations respectively, with a significant reduced design effort and time.

A Configurable Packet Classification Architecture for Software-Defined Networking

Network management tools must be able to monitor and analyze traffic flowing through network systems. According to the OpenFlow protocol applied in Software-Defined Networking (SDN), packets are classified into flows that are searched in flow tables. Further actions, such as packet forwarding, modification, and redirection to a group table, are made in the flow table with respect to the search results. A novel hardware solution for SDN-enabled packet classification is presented in this paper. The proposed scheme is focused on a label-based search method, achieving high flexibility in memory usage. The implemented hardware architecture provides optimal lookup performance by configuring the search algorithm and by performing fast incremental update as programmed the software controller.

Inexact-aware architecture design for ultra-low power bio-signal analysis

This study introduces an inexact, but ultra-low power, computing architecture devoted to the embedded analysis of bio-signals. The platform operates at extremely low voltage supply levels to minimise energy consumption. In this scenario, the reliability of static RAM (SRAM) memories cannot be guaranteed when using conventional 6-transistor implementations. While error correction codes and dedicated SRAM implementations can ensure correct operations in this near-threshold regime, they incur in significant area and energy overheads, and should therefore be employed judiciously. Herein, the authors propose a novel scheme to design inexact computing architectures that selectively protects memory regions based on their significance, i.e. their impact on the end-to-end quality of service, as dictated by the bio-signal application characteristics. The authors illustrate their scheme on an industrial benchmark application performing the power spectrum analysis of electrocardiograms. Experimental evidence showcases that a significance-based memory protection approach leads to a small degradation in the output quality with respect to an exact implementation, while resulting in substantial energy gains, both in the memory and the processing subsystem.

P2P and SOA architecture for digital libraries

In an information-driven society where the volume and value of produced and consumed data assumes a growing importance, the role of digital libraries gains particular importance. This work analyzes the limitations in current digital library management systems and the opportunities brought by recent distributed computing models. The result of this work is the implementation of the University of Aveiro integrated system for digital libraries and archives. It concludes by analyzing the system in production and proposing a new service oriented digital library architecture supported in a peer-to-peer infrastructure