Hardware/software optimizations for elliptic curve scalar multiplication on hybrid FPGAs

Elliptic curve cryptography (ECC) offers a viable alternative to Rivest-Shamir-Adleman (RSA) by delivering equivalent security with a smaller key size. This has several advantages, including smaller bandwidth demands, faster key exchange, and lower latency encryption and decryption. The fundamental operation for ECC is scalar point multiplication, wherein a point P on an elliptic curve defined over a finite field is multiplied by a scalar k. The complexity of this operation requires a hardware implementation to achieve high performance. The algorithms involved in scalar point multiplication are constantly evolving, incorporating the latest developments in number theory to improve computation time. These competing needs, high performance and flexibility, have caused previous implementations to either limit their adaptability or to incur performance losses. This thesis explores the use of a hybrid-FPGA for scalar point multiplication. A hybrid- FPGA contains a general purpose processor (GPP) in addition to reconfigurable fabric. This allows for a software/hardware co-design with low latency communication between the GPP and custom hardware. The elliptic curve operations and finite field inversion are programmed in C code. All other finite field arithmetic is implemented in the FPGA hardware, providing higher performance while retaining flexibility. The resulting implementation achieves speedups ranging from 24 times to 55 times faster than an optimized software implementation executing on a Pentium II workstation. The scalability of the design is investigated in two directions: faster finite field multiplication and increased instruction level parallelism exploitation. Increasing the number of parallel arithmetic units beyond two is shown to be less efficient than increasing the speed of the finite field multiplier

Nothing Lasts Forever: Environmental Discourses on the Collapse of Past Societies

The study of the collapse of past societies raises many questions for the theory and practice of archaeology. Interest in collapse extends as well into the natural sciences and environmental and sustainability policy. Despite a range of approaches to collapse, the predominant paradigm is environmental collapse, which I argue obscures recognition of the dynamic role of social processes that lie at the heart of human communities. These environmental discourses, together with confusion over terminology and the concepts of collapse, have created widespread aporia about collapse and resulted in the creation of mixed messages about complex historical and social processes

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

25th annual computational neuroscience meeting: CNS-2016

The same neuron may play different functional roles in the neural circuits to which it belongs. For example, neurons in the Tritonia pedal ganglia may participate in variable phases of the swim motor rhythms [1]. While such neuronal functional variability is likely to play a major role the delivery of the functionality of neural systems, it is difficult to study it in most nervous systems. We work on the pyloric rhythm network of the crustacean stomatogastric ganglion (STG) [2]. Typically network models of the STG treat neurons of the same functional type as a single model neuron (e.g. PD neurons), assuming the same conductance parameters for these neurons and implying their synchronous firing [3, 4]. However, simultaneous recording of PD neurons shows differences between the timings of spikes of these neurons. This may indicate functional variability of these neurons. Here we modelled separately the two PD neurons of the STG in a multi-neuron model of the pyloric network. Our neuron models comply with known correlations between conductance parameters of ionic currents. Our results reproduce the experimental finding of increasing spike time distance between spikes originating from the two model PD neurons during their synchronised burst phase. The PD neuron with the larger calcium conductance generates its spikes before the other PD neuron. Larger potassium conductance values in the follower neuron imply longer delays between spikes, see Fig. 17.Neuromodulators change the conductance parameters of neurons and maintain the ratios of these parameters [5]. Our results show that such changes may shift the individual contribution of two PD neurons to the PD-phase of the pyloric rhythm altering their functionality within this rhythm. Our work paves the way towards an accessible experimental and computational framework for the analysis of the mechanisms and impact of functional variability of neurons within the neural circuits to which they belong