arXiv subjects

Phillip Stanley-Marbell

Publications and source records attributed to Phillip Stanley-Marbell.

29 records · Page 2Linked to original sources

arXiv2020

Content-Aware Automated Parameter Tuning for Approximate Color Transforms

There are numerous approximate color transforms reported in the literature that aim to reduce display power consumption by imperceptibly changing the color content of displayed images. To be practical, these techniques need to be content-aware in picking transformation parameters to preserve perceptual quality. This work presents a computationally-efficient method for calculating a parameter lower bound for approximate color transform parameters based on the content to be transformed. We conduct a user study with 62 participants and 6,400 image pair comparisons to derive the proposed solution. We use the user study results to predict this lower bound reliably with a 1.6% mean squared error by using simple image-color-based heuristics. We show that these heuristics have Pearson and Spearman rank correlation coefficients greater than 0.7 (p<0.01) and that our model generalizes beyond the data from the user study. The user study results also show that the color transform is able to achieve up to 50% power saving with most users reporting negligible visual impairment.

cs.HC↗

arXiv2020

Inferring Human Observer Spectral Sensitivities from Video Game Data

With the use of primaries which have increasingly narrow bandwidths in modern displays, observer metameric breakdown is becoming a significant factor. This can lead to discrepancies in the perceived color between different observers. If the spectral sensitivity of a user's eyes could be easily measured, next generation displays would be able to adjust the display content to ensure that the colors are perceived as intended by a given observer. We present a mathematical framework for calculating spectral sensitivities of a given human observer using a color matching experiment that could be done on a mobile phone display. This forgoes the need for expensive in-person experiments and allows system designers to easily calibrate displays to match the user's vision, in-the-wild. We show how to use sRGB pixel values along with a simple display model to calculate plausible color matching functions (CMFs) for the users of a given display device (e.g., a mobile phone). We evaluate the effect of different regularization functions on the shape of the calculated CMFs and the results show that a sum of squares regularizer is able to predict smooth and qualitatively realistic CMFs.

q-bio.QM↗

arXiv2020

Automated Physics-Derived Code Generation for Sensor Fusion and State Estimation

We present a new method for automatically generating the implementation of state-estimation algorithms from a machine-readable specification of the physics of a sensing system and physics of its signals and signal constraints. We implement the new state-estimator code generation method as a backend for a physics specification language and we apply the backend to generate complete C code implementations of state estimators for both linear systems (Kalman filters) and non-linear systems (extended Kalman filters). The state estimator code generation from physics specification is completely automated and requires no manual intervention. The generated filters can incorporate an Automatic Differentiation technique which combines function evaluation and differentiation in a single process. Using the description of physical system of a range of complexities, we generate extended Kalman filters, which we evaluate in terms of prediction accuracy using simulation traces. The results show that our automatically-generated sensor fusion and state estimation implementations provide state estimation within the same error bound as the human-written hand-optimized counterparts. We additionally quantify the code size and dynamic instruction count requirements of the generated state estimator implementations on the RISC-V architecture. The results show that our synthesized state estimation implementation employing Automatic Differentiation leads to an average improvement in the dynamic instruction count of the generated Kalman filter of 7%-16% compared to the standard differentiation technique. This is improvement comes at the limited cost of an average 4.5% increase in the code size of the generated filters.

eess.SY↗

arXiv2020

Efficient Programmable Random Variate Generation Accelerator from Sensor Noise

We introduce a method for non-uniform random number generation based on sampling a physical process in a controlled environment. We demonstrate one proof-of-concept implementation of the method that reduces the error of Monte Carlo integration of a univariate Gaussian by 1068 times while doubling the speed of the Monte Carlo simulation. We show that the supply voltage and temperature of the physical process must be controlled to prevent the mean and standard deviation of the random number generator from drifting.

cs.OH↗

arXiv2020

Synthesizing Compact Hardware for Accelerating Inference from Physical Signals in Sensors

We present dimensional circuit synthesis, a new method for generating digital logic circuits that improve the efficiency of training and inference of machine learning models from sensor data. The hardware accelerators that the method generates are compact enough (a few thousand gates) to allow integration within low-cost miniaturized sensor integrated circuits, right next to the sensor transducer. The method takes as input a description of physical properties of relevant signals in the sensor transduction process and generates as output a Verilog register transfer level (RTL) description for a circuit that computes low-level features that exploit the units of measure of the signals in the system. We implement dimensional circuit synthesis as a backend to the compiler for Newton, a language for describing physical systems. We evaluate the backend implementation and the hardware it generates, on descriptions of 7 physical systems. The results show that our implementation of dimensional circuit synthesis generates circuits of as little as 1662 logic cells / 1239 gates for the systems we evaluate. We synthesize the designs generated by the dimensional circuit synthesis compilation backend for a low-power miniature FPGA targeted by its manufacturer at sensor interface applications. The circuits which the method generated use as little as 27% of the resources of the 2.15x2.5 mm FPGA. We measure the power dissipation of the FPGA's isolated core supply rail and show that, driven with a pseudorandom signal input stream, the synthesized designs use as little as 1.0 mW and no more than 5.8 mW. These results show the feasibility of integrating physics-inspired machine learning methods within low-cost miniaturized sensor integrated circuits, right next to the sensor transducer.

cs.AR↗

arXiv2020

Payload-Mass-Aware Trajectory Planning on Multi-User Autonomous Unmanned Aerial Vehicles

Future unmanned aerial vehicles (drones) will be shared by multiple users and will have to operate in conditions where their fully-autonomous function is required. Calculation of a drones trajectory will be important but optimal trajectories cannot be calculated unless mass and flight speed are taken into account. This article presents the case for on-drone trajectory planning in a multi-user dynamic payload mass scenario, allowing a drone to calculate its trajectory with no need for ground control communication. We formulate and investigate on-drone trajectory planning under variable payload mass and flight speed awareness, in cases where it is shared by multiple users or applications. We present efficient solutions using a combination of heuristic and optimization algorithms. To support this investigation, we present a new model for the power dissipation of drone propulsion as a function of speed and payload mass. We evaluate our proposed algorithmic solution on contemporary embedded processors and demonstrate its capability to generate near-optimal trajectories with limited computational overhead (less than 300 milliseconds on an ARM Cortex-A9 SoC).

eess.SY↗

arXiv2018

Newton: A Language for Describing Physics

This article introduces Newton, a specification language for notating the analytic form, units of measure, and sensor signal properties for physical-object-specific invariants and general physical laws. We designed Newton to provide a means for hardware designers (e.g., sensor integrated circuit manufacturers, computing hardware architects, or mechanical engineers) to specify properties of the physical environments in which embedded computing systems will be deployed (e.g., a sensing platform deployed on a bridge versus worn by a human). Compilers and other program analysis tools for embedded systems can use a library interface to the Newton compiler to obtain information about the sensors, sensor signals, and inter-signal relationships imposed by the structure and materials properties of a given physical system. The information encoded within Newton specifications could enable new compile-time transformations that exploit information about the physical world.

cs.PL↗

arXiv2018

Exploiting Errors for Efficiency: A Survey from Circuits to Algorithms

When a computational task tolerates a relaxation of its specification or when an algorithm tolerates the effects of noise in its execution, hardware, programming languages, and system software can trade deviations from correct behavior for lower resource usage. We present, for the first time, a synthesis of research results on computing systems that only make as many errors as their users can tolerate, from across the disciplines of computer aided design of circuits, digital system design, computer architecture, programming languages, operating systems, and information theory. Rather than over-provisioning resources at each layer to avoid errors, it can be more efficient to exploit the masking of errors occurring at one layer which can prevent them from propagating to a higher layer. We survey tradeoffs for individual layers of computing systems from the circuit level to the operating system level and illustrate the potential benefits of end-to-end approaches using two illustrative examples. To tie together the survey, we present a consistent formalization of terminology, across the layers, which does not significantly deviate from the terminology traditionally used by research communities in their layer of focus.

cs.AR↗

arXiv2018

Probabilistic Value-Deviation-Bounded Integer Codes for Approximate Communication

When computing systems can tolerate the effects of errors or erasures in their communicated data values, they can trade this tolerance for improved resource efficiency. One method for enabling this tradeoff in the I/O subsystems of computing systems, is to use channel codes that reduce the power needed to send bits on a channel in exchange for bounded errors and erasures on numeric program values---value-deviation-bounded (VDB) codes. Unlike rate distortion codes, which guarantee a bound on the expected value of channel distortion, the probabilistic VDB codes we present guarantee any desired tail distribution on integer distances of words transmitted over a channel. We extend prior work to present tighter upper bounds on the efficiency for VDB codes. We present a new probabilistic VDB encoder that lowers power dissipation in exchange for bounded channel integer distortions. The code we present takes the peculiar approach of changing the channel bit error rate across the ordinal bit positions in a word to reduce power dissipation. We implement the code table generator in a software tool built on the dReal SMT solver and we validate the generated codes using Monte Carlo simulation. We present one realization of hardware to implement the technique, requiring 2 mm$^2$ of circuit board area and dissipating less than 0.5 $μ$W.

cs.IT↗

arXiv2018

A Hardware Platform for Efficient Multi-Modal Sensing with Adaptive Approximation

We present Warp, a hardware platform to support research in approximate computing, sensor energy optimization, and energy-scavenged systems. Warp incorporates 11 state-of-the-art sensor integrated circuits, computation, and an energy-scavenged power supply, all within a miniature system that is just 3.6 cm x 3.3 cm x 0.5 cm. Warp's sensor integrated circuits together contain a total of 21 sensors with a range of precisions and accuracies for measuring eight sensing modalities of acceleration, angular rate, magnetic flux density (compass heading), humidity, atmospheric pressure (elevation), infrared radiation, ambient temperature, and color. Warp uses a combination of analog circuits and digital control to facilitate further tradeoffs between sensor and communication accuracy, energy efficiency, and performance. This article presents the design of Warp and presents an evaluation of our hardware implementation. The results show how Warp's design enables performance and energy efficiency versus ac- curacy tradeoffs.

physics.app-ph↗

arXiv2018

Incremental Color Quantization for Color-Vision-Deficient Observers Using Mobile Gaming Data

The sizes of compressed images depend on their spatial resolution (number of pixels) and on their color resolution (number of color quantization levels). We introduce DaltonQuant, a new color quantization technique for image compression that cloud services can apply to images destined for a specific user with known color vision deficiencies. DaltonQuant improves compression in a user-specific but reversible manner thereby improving a user's network bandwidth and data storage efficiency. DaltonQuant quantizes image data to account for user-specific color perception anomalies, using a new method for incremental color quantization based on a large corpus of color vision acuity data obtained from a popular mobile game. Servers that host images can revert DaltonQuant's image requantization and compression when those images must be transmitted to a different user, making the technique practical to deploy on a large scale. We evaluate DaltonQuant's compression performance on the Kodak PC reference image set and show that it improves compression by an additional 22%-29% over the state-of-the-art compressors TinyPNG and pngquant.

cs.HC↗