Experiences with implementing common mathematical operations using field programmable gate arrays

Many computationally intensive scientific applications involve repetitive floating point operations other than addition and multiplication which may present a significant performance bottleneck due to the relatively large latency or low throughput involved in executing such arithmetic primitives on commod- ity processors. A promising alternative is to execute such primitives on Field Programmable Gate Array (FPGA) hardware acting as an application-specific custom co-processor in a high performance reconfig- urable computing platform. The use of FPGAs can provide advantages such as fine-grain parallelism but issues relating to code development in a hardware description language and efficient data transfer to and from the FPGA chip can present significant application development challenges. In this paper, we discuss our practical experiences in developing a selection of floating point hardware designs to be implemented using FPGAs. Our designs include some basic mathemati cal library functions which can be implemented for user defined precisions suitable for novel applications requiring non-standard floating point represen- tation. We discuss the details of our designs along with results from performance and accuracy analysis tests.

Solving tri-diagonal linear systems using field programmable gate arrays

In this paper, we present the outcomes of a project on the exploration of the use of Field Programmable Gate Arrays(FPGAs) as co-processors for scientific computation. We designed a custom circuit for the pipelined solving of multiple tri-diagonal linear systems. The design is well suited for applications that require many independent tri diagonal system solves, such as finite difference methods for solving PDEs or applications utilising cubic spline interpolation. The selected solver algorithm was the Tri Diagonal Matrix Algorithm (TDMA or Thomas Algorithm). Our solver supports user specified precision thought the use of a custom floating point VHDL library supporting addition, subtraction, multiplication and division. The variable precision TDMA solver was tested for correctness in simulation mode. The TDMA pipeline was tested successfully in hardware using a simplified solver model. The details of implementation, the limitations, and future work are also discussed.

Solving tri-diagonal linear systems using field programmable gate arrays

In this paper, we present the outcomes of a project on the exploration of the use of Field Programmable Gate Arrays (FPGAs) as co-processors for scientific computation. We designed a custom circuit for the pipelined solving of multiple tri-diagonal linear systems. The design is well suited for applications that require many independent tri-diagonal system solves, such as finite difference methods for solving PDEs or applications utilising cubic spline interpolation. The selected solver algorithm was the Tri-Diagonal Matrix Algorithm (TDMA or Thomas Algorithm). Our solver supports user specified precision thought the use of a custom floating point VHDL library supporting addition, subtraction, multiplication and division. The variable precision TDMA solver was tested for correctness in simulation mode. The TDMA pipeline was tested successfully in hardware using a simplified solver model. The details of implementation, the limitations, and future work are also discussed.

Cohesive zone modelling of mineralized collagen fibril arrays in bending

Hard biological materials such as bone possess superior material properties of high stiffness and toughness. Two unique characteristics of bone microstructure are a large aspect ratio of mineralized collagen fibrils (MCF), and an extremely thin and large area of extrafibrillar protein matrix located between the MCF. The objective of this study is to investigate the effects of: (1) MCF aspect ratio, and (2) energy dissipation in extrafibrillar protein matrix on the mechanical behaviour of MCF arrays. In this study, notched specimens of MCF arrays in extrafibrillar protein matrix are subjected to bending. Cohesive zone model was implemented to simulate the failure of extrafibrillar protein matrix. The study reveals that the MCF array with a higher MCF aspect ratio and the MCF array with a higher protein energy dissipation in the interface direction are able to sustain a higher bending force and dissipate higher energy.

Design, construction, and analysis of cell line arrays and tissue microarrays for gene expression analysis

Cell line array (CMA) and tissue microarray (TMA) technologies are high-throughput methods for analysing both the abundance and distribution of gene expression in a panel of cell lines or multiple tissue specimens in an efficient and cost-effective manner. The process is based on Kononen's method of extracting a cylindrical core of paraffin-embedded donor tissue and inserting it into a recipient paraffin block. Donor tissue from surgically resected paraffin-embedded tissue blocks, frozen needle biopsies or cell line pellets can all be arrayed in the recipient block. The representative area of interest is identified and circled on a haematoxylin and eosin (H&E)-stained section of the donor block. Using a predesigned map showing a precise spacing pattern, a high density array of up to 1,000 cores of cell pellets and/or donor tissue can be embedded into the recipient block using a tissue arrayer from Beecher Instruments. Depending on the depth of the cell line/tissue removed from the donor block 100-300 consecutive sections can be cut from each CMA/TMA block. Sections can be stained for in situ detection of protein, DNA or RNA targets using immunohistochemistry (IHC), fluorescent in situ hybridisation (FISH) or mRNA in situ hybridisation (RNA-ISH), respectively. This chapter provides detailed methods for CMA/TMA design, construction and analysis with in-depth notes on all technical aspects including tips to deal with common pitfalls the user may encounter. © Springer Science+Business Media, LLC 2011.

Hydrogel microwell arrays allow the assessment of protease-associated enhancement of cancer cell aggregation and survival

Current routine cell culture techniques are only poorly suited to capture the physiological complexity of tumor microenvironments, wherein tumor cell function is affected by intricate three-dimensional (3D), integrin-dependent cell-cell and cell-extracellular matrix (ECM) interactions. 3D cell cultures allow the investigation of cancer-associated proteases like kallikreins as they degrade ECM proteins and alter integrin signaling, promoting malignant cell behaviors. Here, we employed a hydrogel microwell array platform to probe using a high-throughput mode how ovarian cancer cell aggregates of defined size form and survive in response to the expression of kallikreins and treatment with paclitaxel, by performing microscopic, quantitative image, gene and protein analyses dependent on the varying microwell and aggregate sizes. Paclitaxel treatment increased aggregate formation and survival of kallikrein-expressing cancer cells and levels of integrins and integrin-related factors. Cancer cell aggregate formation was improved with increasing aggregate size, thereby reducing cell death and enhancing integrin expression upon paclitaxel treatment. Therefore, hydrogel microwell arrays are a powerful tool to screen the viability of cancer cell aggregates upon modulation of protease expression, integrin engagement and anti-cancer treatment providing a micro-scaled yet high-throughput technique to assess malignant progression and drug-resistance.

Generalised cumulative arrays in secret sharing

Cumulative arrays have played an important role in the early development of the secret sharing theory. They have not been subject to extensive study so far, as the secret sharing schemes built on them generally result in much larger sizes of shares, when compared with other conventional approaches. Recent works in threshold cryptography show that cumulative arrays may be the appropriate building blocks in non-homomorphic threshold cryptosystems where the conventional secret sharing methods are generally of no use. In this paper we study several extensions of cumulative arrays and show that some of these extensions significantly improve the performance of conventional cumulative arrays. In particular, we derive bounds on generalised cumulative arrays and show that the constructions based on perfect hash families are asymptotically optimal. We also introduce the concept of ramp perfect hash families as a generalisation of perfect hash families for the study of ramp secret sharing schemes and ramp cumulative arrays.

Ideal threshold schemes from orthogonal arrays

The work investigates the design of ideal threshold secret sharing in the context of cheating prevention. We showed that each orthogonal array is exactly a defining matrix of an ideal threshold scheme. To prevent cheating, defining matrices should be nonlinear so both the cheaters and honest participants have the same chance of guessing of the valid secret. The last part of the work shows how to construct nonlinear secret sharing based on orthogonal arrays.

Atmospheric microplasma-functionalized 3D microfluidic strips within dense carbon nanotube arrays confine Au nanodots for SERS sensing

An atmospheric microplasma jet produces three-dimensional (3D) microfluidic channels on dense arrays of vertically aligned carbon nanotubes, which confines Au nanodot aqueous solution. The resulting hybrid 3D nanostructure is exploited as an effective microscopic area-selective sensing platform based on surface-enhanced Raman scattering.

Physisorption-induced electron scattering on the surface of carbon-metal core-shell nanowire arrays for hydrogen sensing

Palladium is sputtered on multi-walled carbon nanotube forests to form carbon-metal core-shell nanowire arrays. These hybrid nanostructures exhibited resistive responses when exposed to hydrogen with an excellent baseline recovery at room temperature. The magnitude of the response is shown to be tuneable by an applied voltage. Unlike the charge-transfer mechanism commonly attributed to Pd nanoparticle-decorated carbon nanotubes, this demonstrates that the hydrogen response mechanism of the multi-walled carbon nanotube-Pd core-shell nanostructure is due to the increase in electron scattering induced by physisorption of hydrogen. These hybrid core-shell nanostructures are promising for gas detection in hydrogen storage applications.

Ion impact distribution over plasma exposed nanocone arrays

The effect of an ordered array of nanocones on a conducting substrate immersed in the plasma on the transport of the plasma ions is investigated. The real conical shape of the cones is rigorously incorporated into the model. The movement of 10^5 CH3+ ions in the plasma sheath modified by the nanocone array is simulated. The ions are driven by the electric fields produced by the sheath and the nanostructures. The surface charge density and the total charge on the nanotips with different aspect ratios are computed. The ion transport simulation provides important characteristics of the displacement and velocity of the ions. The relative ion distribution along the lateral surfaces of the carbon nanotips is computed as well. It is shown that a rigorous account of the realistic nanostructure shape leads to very different distribution of the ion fluxes on the nanostructured surfaces compared to the previously reported works. The ion flux distribution is a critical factor in the nucleation process on the substrate and determines the nanostructure growth patterns.

Plasma-enabled graded nanotube biosensing arrays on a Si nanodevice platform : catalyst-free integration and in situ detection of nucleation events

Low-temperature plasmas in direct contact with arbitrary, written linear features on a Si wafer enable catalyst-free integration of carbon nanotubes into a Si-based nanodevice platform and in situ resolution of individual nucleation events. The graded nanotube arrays show reliable, reproducible, and competitive performance in electron field emission and biosensing nanodevices.

Uniform, dense arrays of vertically aligned, large-diameter single-walled carbon nanotubes

Precisely controlled reactive chemical vapor synthesis of highly uniform, dense arrays of vertically aligned single-walled carbon nanotubes (SWCNTs) using tailored trilayered Fe/Al2O3/SiO2 catalyst is demonstrated. More than 90% population of thick nanotubes (>3 nm in diameter) can be produced by tailoring the thickness and microstructure of the secondary catalyst supporting SiO2 layer, which is commonly overlooked. The proposed model based on the atomic force microanalysis suggests that this tailoring leads to uniform and dense arrays of relatively large Fe catalyst nanoparticles on which the thick SWCNTs nucleate, while small nanotubes and amorphous carbon are effectively etched away. Our results resolve a persistent issue of selective (while avoiding multiwalled nanotubes and other carbon nanostructures) synthesis of thick vertically aligned SWCNTs whose easily switchable thickness-dependent electronic properties enable advanced applications in nanoelectronic, energy, drug delivery, and membrane technologies.

Control of density of self-organized carbon nanotube arrays by catalyst pretreatment through plasma immersion ion implantation

A simple and effective method of controlling the growth of vertically aligned carbon nanotube arrays in a lowerature plasma is presented. Ni catalyst was pretreated by plasma immersion ion implantation prior to the nanotube growth by plasma-enhanced chemical vapor deposition. Both the size distribution and the areal density of the catalyst nanoparticles decrease due to the ion-surface interactions. Consequently, the resulting size distribution of the vertically aligned carbon nanotubes is reduced to 50 ∼ 100 nm and the areal density is lowered (by a factor of ten) to 10 8 cm -2, which is significantly different from the very-high-density carbon nanotube forests commonly produced by thermal chemical vapor deposition. The efficiency of this pretreatment is compared with the existing techniques such as neutral gas annealing and plasma etching. These results are highly relevant to the development of the next-generation nanoelectronic and optoelectronic devices that require effective control of the density of nanotube arrays.

Self-organization in arrays of surface-grown nanoparticles : characterization, control, driving forces

Some important issues related to the self-organization in the arrays of nanoparticles on solid surfaces exposed to the low-temperature plasma are analysed and discussed. The available tools for the characterization of the size and position uniformity in nanoarrays are examined. The technique capable of revealing the realistic adsorbed atom and adsorbed radical capture zone pattern based on the surface physics is indicated as the most promising characterization tool. The processes responsible for the self-organization are analysed, the main driving forces of the self-organization are discussed, and possible ways to control the self-organization by controlling the plasma parameters are introduced. A view on the possible ways to further improve the methods of nanoarray characterization and self-organization is presented as well.