High Speed FPGA-based implementations of Delayed-LMS filters

A variation of the least means squares (LMS) algorithm, called the delayed LMS (DLMS) algorithm is an ideally suited to achieve highly pipelined, adaptive digital filter implementations. The paper presents an efficient method of determining the delays in the DLMS filter and then transferring these delays using retiming in order to achieve fully pipelined circuit architectures for FPGA implementation. The method has been used to derive a series of retimed delayed LMS (RDLMS) architectures, which considerable reduce the number of delays and convergence time and give superior performance in terms of throughput rate when compared to previous work. Three circuit architectures and three hardware shared versions are presented which have been implemented using the Virtex-II FPGA technology resulting in a throughout rate of 182 Msample/s.

Low power field programmable gate array implementation of fast digital signal processing algorithms: characterisation and manipulation of data locality

Dynamic power consumption is very dependent on interconnect, so clever mapping of digital signal processing algorithms to parallelised realisations with data locality is vital. This is a particular problem for fast algorithm implementations where typically, designers will have sacrificed circuit structure for efficiency in software implementation. This study outlines an approach for reducing the dynamic power consumption of a class of fast algorithms by minimising the index space separation; this allows the generation of field programmable gate array (FPGA) implementations with reduced power consumption. It is shown how a 50% reduction in relative index space separation results in a measured power gain of 36 and 37% over a Cooley-Tukey Fast Fourier Transform (FFT)-based solution for both actual power measurements for a Xilinx Virtex-II FPGA implementation and circuit measurements for a Xilinx Virtex-5 implementation. The authors show the generality of the approach by applying it to a number of other fast algorithms namely the discrete cosine, the discrete Hartley and the Walsh-Hadamard transforms.

Very high speed 17 Gbps SHACAL encryption architecture

Very high speed and low area hardware architectures of the SHACAL-1 encryption algorithm are presented in this paper. The SHACAL algorithm was a submission to the New European Schemes for Signatures, Integrity and Encryption (NESSIE) project and it is based on the SHA-1 hash algorithm. To date, there have been no performance metrics published on hardware implementations of this algorithm. A fully pipelined SHACAL-1 encryption architecture is described in this paper and when implemented on a Virtex-II X2V4000 FPGA device, it runs at a throughput of 17 Gbps. A fully pipelined decryption architecture achieves a speed of 13 Gbps when implemented on the same device. In addition, iterative architectures of the algorithm are presented. The SHACAL-1 decryption algorithm is derived and also presented in this paper, since it was not provided in the submission to NESSIE. © Springer-Verlag Berlin Heidelberg 2003.

Pellino3 targets RIP1 and regulates the pro-apoptotic effects of TNF-∝

Tumour necrosis factor-a (TNF) can activate NF-?B to induce pro-inflammatory genes but can also stimulate the caspase cascade to promote apoptosis. Here we show that deficiency of the ubiquitin E3 ligase, Pellino3, sensitizes cells to TNF-induced apoptosis without inhibiting the NF-?B pathway. Suppressed expression of Pellino3 leads to enhanced formation of the death-induced signalling complex, complex II, in response to TNF. We show that Pellino3 targets RIP1, in a TNF-dependent manner, to inhibit TNF-induced complex II formation and caspase 8-mediated cleavage of RIP1 in response to TNF/cycloheximide co-stimulation. Pellino3-deficient mice also show increased sensitivity to TNF-induced apoptosis and greatly increased lethality in response to TNF administration. These findings define Pellino3 as a novel regulator of TNF signalling and an important determining factor in dictating whether TNF induces cell survival or death.