Cross-Platform OpenCL Code and Performance Portability Investigated with a Climate and Weather Physics Model

2012 ◽  
Author(s):  
Han Dong ◽  
Dibyajyoti Ghosh ◽  
Fahad Zafar ◽  
Shujia Zhou
Keyword(s):  
Performance Portability ◽  
Cross Platform ◽  
And Performance ◽  
Physics Model

scholarly journals Programmability and performance portability aspects of heterogeneous multi-/manycore systems

2012 ◽  
Author(s):  
C. Kessler ◽  
U. Dastgeer ◽  
S. Thibault ◽  
R. Namyst ◽  
A. Richards ◽  
...  
Keyword(s):  
Performance Portability ◽  
And Performance

scholarly journals Animations in Cross-Platform Mobile Applications: An Evaluation of Tools, Metrics and Performance

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2081 ◽  
Author(s):  
Andreas Biørn-Hansen ◽  
Tor-Morten Grønli ◽  
Gheorghita Ghinea
Keyword(s):  
User Interfaces ◽  
Mobile Apps ◽  
Memory Usage ◽  
Performance Profiling ◽  
App Development ◽  
Cpu Usage ◽  
Cross Platform ◽  
Platform Development ◽  
And Performance ◽  
The Impact

Along with the proliferation of high-end and performant mobile devices, we find that the inclusion of visually animated user interfaces are commonplace, but that research on their performance is scarce. Thus, for this study, eight mobile apps have been developed for scrutiny and assessment to report on the device hardware impact and penalties caused by transitions and animations, with an emphasis on apps generated using cross-platform development frameworks. The tasks we employ for animation performance measuring, are those of (i) a complex animation consisting of multiple elements, (ii) the opening sequence of a side menu navigation pattern, and (iii) a transition animation during in-app page navigation. We employ multiple performance profiling tools, and scrutinize metrics including frames per second (FPS), CPU usage, device memory usage and GPU memory usage, all to uncover the impact caused by executing transitions and animations. We uncover important differences in device hardware utilization during animations across the different cross-platform technologies employed. Additionally, Android and iOS are found to differ greatly in terms of memory consumption, CPU usage and rendered FPS, a discrepancy that is true for both the native and cross-platform apps. The findings we report are indeed factors contributing to the complexity of app development.

scholarly journals СROSS PLATFORM TOOLS FOR MODELING AND RECOGNITION OF THE FINGERSPELLING ALPHABET OF GESTURE LANGUAGE

2019 ◽  
Vol 9 (2) ◽  
pp. 24-27
Author(s):  
Serhii Kondratiuk ◽  
Iurii Krak ◽  
Waldemar Wójcik
Keyword(s):  
Recognition Performance ◽  
Internet Connection ◽  
Hand Model ◽  
Sign Recognition ◽  
Recognition Experiment ◽  
Cross Platform ◽  
Model Size ◽  
Language Modelling ◽  
And Performance ◽  
Experimental Researches

A solution for the problems of the finger spelling alphabet of gesture language modelling and recognition based on cross-platform technologies is proposed. Modelling and recognition performance can be flexible and adjusted, based on the hardware it operates or based on the availability of an internet connection. The proposed approach tunes the complexity of the 3D hand model based on the CPU type, amount of available memory and internet connection speed. Sign recognition is also performed using cross-platform technologies and the tradeoff in model size and performance can be adjusted. the methods of convolutional neural networks are used as tools for gestures of alphabet recognition. For the gesture recognition experiment, a dataset of 50,000 images was collected, with 50 different hands recorded, with almost 1,000 images per each person. The experimental researches demonstrated the effectiveness of proposed approaches.

scholarly journals Simulator Coupled with Distributed Co-Simulation Protocol for Automated Driving Tests

2021 ◽  
Author(s):  
Max-Arno Meyer ◽  
Lina Sauter ◽  
Christian Granrath ◽  
Hassen Hadj-Amor ◽  
Jakob Andert
Keyword(s):  
Data Exchange ◽  
Time Synchronization ◽  
Simulation Models ◽  
Simulation Platform ◽  
Automated Driving ◽  
Complex Simulation ◽  
Simulation Protocol ◽  
Environment Simulation ◽  
Cross Platform ◽  
And Performance

AbstractTo meet the challenges in software testing for automated vehicles, such as increasing system complexity and an infinite number of operating scenarios, new simulation methods must be developed. Closed-loop simulations for automated driving (AD) require highly complex simulation models for multiple controlled vehicles with their perception systems as well as their surrounding context. For the realization of such models, different simulation domains must be coupled with co-simulation. However, widely supported model integration standards such as functional mock-up interface (FMI) lack native support for distributed platforms, which is a key feature for AD due to the computational intensity and platform exclusivity of certain models. The newer FMI companion standard distributed co-simulation protocol (DCP) introduces platform coupling but must still be used in conjunction with AD co-simulations. As part of an assessment framework for AD, this paper presents a DCP compliant implementation of an interoperable interface between a 3D environment and vehicle simulator and a co-simulation platform. A universal Python wrapper is implemented and connected to the simulator to allow its control as a DCP slave. A C-code-based interface enables the co-simulation platform to act as a DCP master and to realize cross-platform data exchange and time synchronization of the environment simulation with other integrated models. A model-in-the-loop use case is performed with the traffic simulator CARLA running on a Linux machine connected to the co-simulation master xMOD on a Windows computer via DCP. Several virtual vehicles are successfully controlled by cooperative adaptive cruise controllers executed outside of CARLA. The standard compliance of the implementation is verified by exemplary connection to prototypic DCP solutions from 3rd party vendors. This exemplary application demonstrates the benefits of DCP compliant tool coupling for AD simulation with increased tool interoperability, reuse potential, and performance.

scholarly journals Cross-Platform Evaluation of Commercially Targeted and Untargeted Metabolomics Approaches to Optimize the Investigation of Psychiatric Disease

Metabolites ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 609
Author(s):  
Lauren E. Chaby ◽  
Heather C. Lasseter ◽  
Kévin Contrepois ◽  
Reza M. Salek ◽  
Christoph W. Turck ◽  
...  
Keyword(s):  
Fatty Acids ◽  
Stress Disorder ◽  
Psychiatric Disease ◽  
Trade Offs ◽  
Specific Performance ◽  
Cross Platform ◽  
Quantification Accuracy ◽  
Precision And Accuracy ◽  
Assay Precision ◽  
And Performance

Metabolomics methods often encounter trade-offs between quantification accuracy and coverage, with truly comprehensive coverage only attainable through a multitude of complementary assays. Due to the lack of standardization and the variety of metabolomics assays, it is difficult to integrate datasets across studies or assays. To inform metabolomics platform selection, with a focus on posttraumatic stress disorder (PTSD), we review platform use and sample sizes in psychiatric metabolomics studies and then evaluate five prominent metabolomics platforms for coverage and performance, including intra-/inter-assay precision, accuracy, and linearity. We found performance was variable between metabolite classes, but comparable across targeted and untargeted approaches. Within all platforms, precision and accuracy were highly variable across classes, ranging from 0.9–63.2% (coefficient of variation) and 0.6–99.1% for accuracy to reference plasma. Several classes had high inter-assay variance, potentially impeding dissociation of a biological signal, including glycerophospholipids, organooxygen compounds, and fatty acids. Coverage was platform-specific and ranged from 16–70% of PTSD-associated metabolites. Non-overlapping coverage is challenging; however, benefits of applying multiple metabolomics technologies must be weighed against cost, biospecimen availability, platform-specific normative levels, and challenges in merging datasets. Our findings and open-access cross-platform dataset can inform platform selection and dataset integration based on platform-specific coverage breadth/overlap and metabolite-specific performance.

scholarly journals An Auto-Programming Approach to Vulkan

2021 ◽  
Author(s):  
Vladimir Alexandrovich Frolov ◽  
Vadim Sanzharov ◽  
Vladimir Alexandrovich Galaktionov ◽  
Alexandr Scherbakov
Keyword(s):  
Performance Studies ◽  
General Purpose ◽  
Software Implementation ◽  
Programming Approach ◽  
Fine Grained ◽  
Speed Up ◽  
Cross Platform ◽  
Increase Productivity ◽  
And Performance ◽  
High Level

We propose a novel high-level approach for software development on GPU using Vulkan API. Our goal is to speed-up development and performance studies for complex algorithms on GPU, which is quite difficult and laborious for Vulkan due to large number of HW features low level details. The proposed approach uses auto programming to translate ordinary C++ to optimized Vulkan implementation with automatic shaders generation, resource binding and fine-grained barriers placement. Our model is not general-purpose programming, but is extendible and customer-focused. For a single C++ input our tool can generate multiple different implementations of algorithm in Vulkan for different cases or types of hardware. For example, we automatically detect reduction in C++ source code and then generate several variants of parallel reduction on GPU: with optimization for different warp size, with or without atomics, using or not subgroup operations. Another example is GPU ray tracing applications for which we can generate different variants: pure software implementation in compute shader, using hardware accelerated ray queries, using full RTX pipeline. The goal of our work is to increase productivity of developers who are forced to use Vulkan due to various required hardware features in their software but still do care about cross-platform ability of the developed software and want to debug their algorithm logic on the CPU. Therefore, we assume that the user will take generated code and integrate it with hand-written Vulkan code.

OpenVX Integration Into the Visual Development Environment

2018 ◽  
Vol 9 (1) ◽  
pp. 20-49 ◽  
Author(s):  
Alexey Syschikov ◽  
Boris Sedov ◽  
Konstantin Nedovodeev ◽  
Vera Ivanova
Keyword(s):  
Computer Vision ◽  
Performance Analysis ◽  
Automatic Generation ◽  
Visual Programming ◽  
Visual Development ◽  
Development Environment ◽  
Performance Portability ◽  
Programming Support ◽  
And Performance ◽  
Performance Analysis Tools

The OpenVX standard has appeared as an answer from the computer vision community to the challenge of accelerating vision applications on embedded heterogeneous platforms. It is designed to leverage the computer vision hardware potential with functional and performance portability. As long as VIPE has a powerful model of computation, it can incorporate various other models. This allows to extend facilities of a language or framework that is based on the model to be incorporated with visual programming support and provide access to the existing performance analysis and deployment tools. The authors present OpenVX integration into the VIPE IDE. VIPE addresses the need to design OpenVX graphs in a natural visual form with automatic generation of a full-fledged program, shielding a programmer from writing a bunch of boilerplate code. To the best of the authors' knowledge, this is the first use of a graphical notation for OpenVX programming. Using VIPE to develop OpenVX programs also enables the performance analysis tools.

Enhancing the Programmability and Performance Portability of GPU Tensor Operations

2019 ◽  
pp. 213-226 ◽  
Author(s):  
Arya Mazaheri ◽  
Johannes Schulte ◽  
Matthew W. Moskewicz ◽  
Felix Wolf ◽  
Ali Jannesari
Keyword(s):  
Performance Portability ◽  
And Performance
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