Advancing source-level timing simulation using loop acceleration

2018 ◽  
Author(s):  
Joscha Benz ◽  
Christoph Gerum ◽  
Oliver Bringmann
Keyword(s):  
Source Level ◽  
Timing Simulation ◽  
Loop Acceleration

scholarly journals Scenario-Aware Program Specialization for Timing Predictability

2021 ◽  
Vol 18 (4) ◽  
pp. 1-26
Author(s):  
Joscha Benz ◽  
Oliver Bringmann
Keyword(s):  
Program Analysis ◽  
Control Flow ◽  
Wcet Analysis ◽  
Specific System ◽  
Worst Case ◽  
Program Specialization ◽  
Operating Modes ◽  
Source Level ◽  
Dependent Flow ◽  
Timing Simulation

The successful application of static program analysis strongly depends on flow facts of a program such as loop bounds, control-flow constraints, and operating modes. This problem heavily affects the design of real-time systems, since static program analyses are a prerequisite to determine the timing behavior of a program. For example, this becomes obvious in worst-case execution time (WCET) analysis, which is often infeasible without user-annotated flow facts. Moreover, many timing simulation approaches use statically derived timings of partial program paths to reduce simulation overhead. Annotating flow facts on binary or source level is either error-prone and tedious, or requires specialized compilers that can transform source-level annotations along with the program during optimization. To overcome these obstacles, so-called scenarios can be used. Scenarios are a design-time methodology that describe a set of possible system parameters, such as image resolutions, operating modes, or application-dependent flow facts. The information described by a scenario is unknown in general but known and constant for a specific system. In this article, 1 we present a methodology for scenario-aware program specialization to improve timing predictability. Moreover, we provide an implementation of this methodology for embedded software written in C/C++. We show the effectiveness of our approach by evaluating its impact on WCET analysis using almost all of TACLeBench–achieving an average reduction of WCET of 31%. In addition, we provide a thorough qualitative and evaluation-based comparison to closely related work, as well as two case studies.

scholarly journals A Reference Spectrum Model for Estimating Source Levels of Marine Shipping Based on Automated Identification System Data

2021 ◽  
Vol 9 (4) ◽  
pp. 369 ◽  
Author(s):  
Alexander MacGillivray ◽  
Christ de Jong
Keyword(s):  
Objective Assessment ◽  
Noise Pollution ◽  
Specific Reference ◽  
Identification System ◽  
Reference Spectrum ◽  
Underwater Sound ◽  
The North ◽  
Joint Monitoring ◽  
Source Level ◽  
Spectrum Model

Underwater sound mapping is increasingly being used as a tool for monitoring and managing noise pollution from shipping in the marine environment. Sound maps typically rely on tracking data from the Automated Information System (AIS), but information available from AIS is limited and not easily related to vessel noise emissions. Thus, robust sound mapping tools not only require accurate models for estimating source levels for large numbers of marine vessels, but also an objective assessment of their uncertainties. As part of the Joint Monitoring Programme for Ambient Noise in the North Sea (JOMOPANS) project, a widely used reference spectrum model (RANDI 3.1) was validated against statistics of monopole ship source level measurements from the Vancouver Fraser Port Authority-led Enhancing Cetacean Habitat and Observation (ECHO) Program. These validation comparisons resulted in a new reference spectrum model (the JOMOPANS-ECHO source level model) that retains the power-law dependence on speed and length but incorporates class-specific reference speeds and new spectrum coefficients. The new reference spectrum model calculates the ship source level spectrum, in decidecade bands, as a function of frequency, speed, length, and AIS ship type. The statistical uncertainty (standard deviation of the deviation between model and measurement) in the predicted source level spectra of the new model is estimated to be 6 dB.

scholarly journals Hindcasting Soundscapes before and during the COVID-19 Pandemic in Selected Areas of the North Sea and the Adriatic Sea

2021 ◽  
Vol 9 (7) ◽  
pp. 702
Author(s):  
Hüseyin Özkan Sertlek
Keyword(s):  
North Sea ◽  
Adriatic Sea ◽  
Propagation Model ◽  
The North ◽  
Fishing Vessels ◽  
Water Test ◽  
The North Sea ◽  
Monthly Changes ◽  
Source Level ◽  
Sound Maps

The national measures in several European countries during the COVID-19 pandemic also affected offshore human activities, including shipping. In this work, the temporal and spatial variations of shipping sound are calculated for the years before and during the pandemic in selected shallow water test areas from the Southern North Sea and the Adriatic Sea. First, the monthly sound pressure level maps of ships and wind between 2017 and 2020 are calculated for frequencies between 100 Hz to 10 kHz. Next, the monthly changes in these maps are compared. The asymptotic approximation of the hybrid flux-mode propagation model reduces the computational requirements for sound mapping simulations and facilitates the production of a large number of sound maps for different months, depths, frequencies, and ship categories. After the strictest COVID-19 measures were applied in April 2020, the largest decline was observed for the fishing, passenger and recreational ships. Although the changes in the number of fishing vessels are large, their contribution to the soundscape is minor due to their low source level. In both test areas, the spatial exceedance levels and acoustic energies were decreased in 2020 compared to the average of the previous three years.

scholarly journals Pattern discovery and disentanglement on relational datasets

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Andrew K. C. Wong ◽  
Pei-Yuan Zhou ◽  
Zahid A. Butt
Keyword(s):  
Machine Learning ◽  
Knowledge Base ◽  
Case Studies ◽  
Prediction Accuracy ◽  
Pattern Discovery ◽  
Explicit Representation ◽  
Human Cognition ◽  
Source Level ◽  
Low Volume

AbstractMachine Learning has made impressive advances in many applications akin to human cognition for discernment. However, success has been limited in the areas of relational datasets, particularly for data with low volume, imbalanced groups, and mislabeled cases, with outputs that typically lack transparency and interpretability. The difficulties arise from the subtle overlapping and entanglement of functional and statistical relations at the source level. Hence, we have developed Pattern Discovery and Disentanglement System (PDD), which is able to discover explicit patterns from the data with various sizes, imbalanced groups, and screen out anomalies. We present herein four case studies on biomedical datasets to substantiate the efficacy of PDD. It improves prediction accuracy and facilitates transparent interpretation of discovered knowledge in an explicit representation framework PDD Knowledge Base that links the sources, the patterns, and individual patients. Hence, PDD promises broad and ground-breaking applications in genomic and biomedical machine learning.

scholarly journals Estimation of the Noise Source Level of a Commercial Ship Using On-Board Pressure Sensors

2021 ◽  
Vol 11 (3) ◽  
pp. 1243
Author(s):  
Hongseok Jeong ◽  
Jeung-Hoon Lee ◽  
Yong-Hyun Kim ◽  
Hanshin Seol
Keyword(s):  
Noise Source ◽  
Pressure Sensors ◽  
Low Frequency ◽  
Frequency Resolution ◽  
Source Strength ◽  
Recording Time ◽  
Source Level ◽  
The One ◽  
Hydrophone Array ◽  
Good Agreement

The dominant underwater noise source of a ship is known to be propeller cavitation. Recently, attempts have been made to quantify the source strength using on-board pressure sensors near the propeller, as this has advantages over conventional noise measurement. In this study, a beamforming method was used to estimate the source strength of a cavitating propeller. The method was validated against a model-scale measurement in a cavitation tunnel, which showed good agreement between the measured and estimated source levels. The method was also applied to a full-scale measurement, in which the source level was measured using an external hydrophone array. The estimated source level using the hull pressure sensors showed good agreement with the measured one above 400 Hz, which shows potential for noise monitoring using on-board sensors. A parametric study was carried out to check the practicality of the method. From the results, it was shown that a sufficient recording time is required to obtain a consistent level at high frequencies. Changing the frequency resolution had little effect on the result, as long as enough data were provided for the one-third octave band conversion. The number of sensors affected the mid- to low-frequency data.

DOC: a practical approach to source-level debugging of globally optimized code

1988 ◽  
Vol 23 (7) ◽  
pp. 125-134 ◽  
Author(s):  
D. S. Coutant ◽  
S. Meloy ◽  
M. Ruscetta
Keyword(s):  
Practical Approach ◽  
Source Level ◽  
Optimized Code
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