Recursive Compressed Sensing

We introduce a recursive algorithm for performing compressed sensing on streaming data. The approach consists of a) recursive encoding, where we sample the input stream via overlapping windowing and make use of the previous measurement in obtaining the next one, and b) recursive decoding, where the signal estimate from the previous window is utilized in order to achieve faster convergence in an iterative optimization scheme applied to decode the new one. To remove estimation bias, a two-step estimation procedure is proposed comprising support set detection and signal amplitude estimation. Estimation accuracy is enhanced by a non-linear voting method and averaging estimates over multiple windows. We analyze the computational complexity and estimation error, and show that the normalized error variance asymptotically goes to zero for sublinear sparsity. Our simulation results show speed up of an order of magnitude over traditional CS, while obtaining significantly lower reconstruction error under mild conditions on the signal magnitudes and the noise level.Comment: Submitted to IEEE Transactions on Information Theor

Mobile App Acceleration via Fine-Grain Offloading to the Cloud

Mobile device hardware can limit the sophistication of mobile applications. One strategy for side-stepping these constraints is to opportunistically offload computations to the cloud, where more capable hardware can do the heavy lifting. We propose a platform that accomplishes this via compressive offloading, a novel application of compressive sensing in a distributed shared memory setting. Our prototype gives up to an order-of-magnitude acceleration and 60% longer battery life to the end user of an example handwriting recognition app. We argue that offloading is beneficial to both end users and cloud providers—the former experiences a performance boost and the latter receives a steady stream of small computations to fill periods of under-utilization. Such workloads, originating from ARM-based mobile devices, are especially well-suited for offloading to emerging ARM-based data centers.Engineering and Applied Science

Cherenkov Gamma Ray Detectors on High-Energy-Density Systems

High energy density (HED) systems are some of the most extreme environments ever created by mankind. Systems with pressures greater than 1 MBar can only be created by a handful of devices on earth, often utilizing high intensity lasers or pulsed power machines. HED systems offer a view into an extreme form of matter only seen in stellar cores, supernovas and other powerful astrophysical systems. Creating HED systems on Earth offer the possibility, if the physics and technology can be matured, to one day create a fusion power plant. If a system is hot and dense enough, the fusion reaction can drive more fusion reactions through the alpha particle depositing its energy. There has been a generation goal of getting this fusion chain reaction to create high yield and gain, however, this regime, called ignition, has remained elusive. Diagnosing HED systems to understand the degradation preventing ignition presents a challenge. HED pockets are often short lived (nanoseconds or picoseconds) and concurrent with a release of a physical blast shock, nuclear particles, a strong electromagnetic pulse and a noisy radiation environment. Cherenkov detectors to measure energy thresholded, time resolved gamma rays is one such technique that can be applied to these systems to gain insight and understanding to the properties of HED systems. In this dissertation, the fundamentals and background of this diagnostic technique are applied in detail to three HED systems. Gas Cherenkov detectors are applied onto the National Ignition Facility\u27s inertial confinement fusion ignition campaigns. Inertial confinement fusion uses high powered lasers to compress a capsule full of deuterium-tritium fuel surrounding by a carbon ablator shell, which is used to push the fuel into high densities and temperatures. A technique to isolate a 4.4 MeV carbon gamma ray is introduced and applied to understand the areal density and compression of the outside portion of the inertial confinement fusion pusher. The new data reveals that the outside portion of the pusher followed the expected hydrodynamic predicted trends, while the inner fuel portion of the pusher looks to be degraded and less compressible. This data suggests for specific degradation mechanisms acting on the capsule that preferentially degrade the fuel, such as ablator-ice mix. The time resolution of the gamma detector also gives information about the velocity of the carbon ablator during the fusion burn. Second, gamma ray measure mix studied field on the OMEGA laser system are shared, showing a complicated mix landscape for spherical implosions. Aerogel Cherenkov detectors are fielded on the Mercury pulsed power facility at the Naval Research Lab which creates an accelerated electron beam to create a strong bremsstrahlung x-ray source. The Aerogel Cherenkov detectors are able to characterize and measure time resolved signals of the x-ray pulse, vital information for the x-ray pulse to be feed into a radiography or photofission source. This dissertation presents a body of work that applies a diagnostic technique to an extreme experimental conditions, receives novel measurements and interprets their results