FPGA acceleration of reference-based compression for genomic data

One of the key challenges facing genomics today is efficiently storing the massive amounts of data generated by next-generation sequencing platforms. Reference-based compression is a popular strategy for reducing the size of genomic data, whereby sequence information is encoded as a mapping to a known reference sequence. Determining the mapping is a computationally intensive problem, and is the bottleneck of most reference-based compression tools currently available. This paper presents the first FPGA acceleration of reference-based compression for genomic data. We develop a new mapping algorithm based on the FM-index search operation which includes optimisations targeting the compression ratio and speed. Our hardware design is implemented on a Maxeler MPC-X2000 node comprising 8 Altera Stratix V FPGAs. When evaluated against compression tools currently available, our tool achieves a superior compression ratio, compression time, and energy consumption for both FASTA and FASTQ formats. For example, our tool achieves a 30% higher compression ratio and is 71.9 times faster than the fastqz tool

Parallelisation of sequential Monte Carlo for real-time control in air traffic management

This paper presents the parallelisation of a Sequential Monte Carlo algorithm, and the associated changes required when applied to the problem of conflict resolution and aircraft trajectory control in air traffic management. The target problem is non-linear, constrained, non-convex and multi-agent. The new method is shown to have a 98.5% computational time saving over that of a previous sequential implementation, with no degradation in path quality. The computation saving is enough to allow real-time implementation.This work was supported by EPSRC (Engineering and Physical Sciences Research Council - UK) Grant No. EP/G066477/1In proceedings of the IEEE Conference on Decision and Control 201

Control of aircraft in the terminal manoeuvring area using parallelised sequential Monte Carlo

This paper reports on the use of a parallelised Model Predictive Control, Sequential Monte Carlo algorithm for solving the problem of conflict resolution and aircraft trajectory control in air traffic management specifically around the terminal manoeuvring area of an airport. The target problem is nonlinear, highly constrained, non-convex and uses a single decision-maker with multiple aircraft. The implementation includes a spatio-temporal wind model and rolling window simulations for realistic ongoing scenarios. The method is capable of handling arriving and departing aircraft simultaneously including some with very low fuel remaining. A novel flow field is proposed to smooth the approach trajectories for arriving aircraft and all trajectories are planned in three dimensions. Massive parallelisation of the algorithm allows solution speeds to approach those required for real-time use.This work was supported by EPSRC (Engineering and Physical Sciences Research Council - UK) Grant No. EP/G066477/1AIAA Conference on Guidance, Navigation and Control 201

Delay-Bounded Routing for Shadow Registers

The on-chip timing behaviour of synchronous circuits can be quantified at run-time by adding shadow registers, which allow designers to sample the most critical paths of a circuit at a different point in time than the user register would normally. In order to sample these paths precisely, the path skew between the user and the shadow register must be tightly controlled and consistent across all paths that are shadowed. Unlike a custom IC, FPGAs contain prefabricated resources from which composing an arbitrary routing delay is not trivial. This paper presents a method for inserting shadow registers with a minimum skew bound, whilst also reducing the maximum skew. To preserve circuit timing, we apply this to FPGA circuits post place-and-route, using only the spare resources left behind. We find that our techniques can achieve an average STA reported delay bound of ±200ps on a Xilinx device despite incomplete timing information, and achieve <1ps accuracy against our own delay model

White Paper: Measuring the Neutrino Mass Hierarchy

This white paper is a condensation of a report by a committee appointed jointly by the Nuclear Science and Physics Divisions at Lawrence Berkeley National Laboratory (LBNL). The goal of this study was to identify the most promising technique(s) for resolving the neutrino mass hierarchy. For the most part, we have relied on calculations and simulations presented by the proponents of the various experiments. We have included evaluations of the opportunities and challenges for these experiments based on what is available already in the literature.Comment: White paper prepared for Snowmass-201

MICROFRACTURE OF HUMAN THORACOLUMBAR VERTEBRAL BODY UNDER FATIGUE LOADING

The purpose of this study was to investigate the relationship between lumbar vertebral microfracture and fatigue loading on young human spine under physiological cyclic compression loads. Thirty-three thoracolumbar vertebrae (T12 to L4) were obtained from 7 adult Chinese male cadavers. They were randomly divided into 5 groups. Cyclical compression was performed for 20,000 cycles with 2 Hz. Load magnitude was determined respectively as 10%, 20% and 30% of the ultimate compressive load. Four cylindrical sections were obtained from each vertebra and the cross-sectional slides were made. The histomorphometry was used to determine microfracture densitiy and distribution. No fracture was detected in the radiographs of groups III, IV and V after fatigue load. Microfracture density in the cyclic compression group increased from 0.46 #/mm2 in Group III to 0.66 #/mm2 (Group IV) and 0.94 #/mm2 (Group V) under different loading levels (). These results provide evidence for the existence of microfractures caused by fatigue loads that are undetectable by X-ray

Mapping adaptive particle filters to heterogeneous reconfigurable systems

This article presents an approach for mapping real-time applications based on particle filters (PFs) to heterogeneous reconfigurable systems, which typically consist of multiple FPGAs and CPUs. A method is proposed to adapt the number of particles dynamically and to utilise runtime reconfigurability of FPGAs for reduced power and energy consumption. A data compression scheme is employed to reduce communication overhead between FPGAs and CPUs. A mobile robot localisation and tracking application is developed to illustrate our approach. Experimental results show that the proposed adaptive PF can reduce up to 99% of computation time. Using runtime reconfiguration, we achieve a 25% to 34% reduction in idle power. A 1U system with four FPGAs is up to 169 times faster than a single-core CPU and 41 times faster than a 1U CPU server with 12 cores. It is also estimated to be 3 times faster than a system with four GPUs

The Radon Monitoring System in Daya Bay Reactor Neutrino Experiment

We developed a highly sensitive, reliable and portable automatic system (H$^{3}$) to monitor the radon concentration of the underground experimental halls of the Daya Bay Reactor Neutrino Experiment. H$^{3}$ is able to measure radon concentration with a statistical error less than 10\% in a 1-hour measurement of dehumidified air (R.H. 5\% at 25$^{\circ}$C) with radon concentration as low as 50 Bq/m$^{3}$. This is achieved by using a large radon progeny collection chamber, semiconductor $\alpha$-particle detector with high energy resolution, improved electronics and software. The integrated radon monitoring system is highly customizable to operate in different run modes at scheduled times and can be controlled remotely to sample radon in ambient air or in water from the water pools where the antineutrino detectors are being housed. The radon monitoring system has been running in the three experimental halls of the Daya Bay Reactor Neutrino Experiment since November 2013