• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 61844
  • 6049
  • 5658
  • 3723
  • 3450
  • 2277
  • 2277
  • 2277
  • 2277
  • 2277
  • 2264
  • 1227
  • 1148
  • 643
  • 535
  • Tagged with
  • 103716
  • 45478
  • 28914
  • 20559
  • 17967
  • 12470
  • 10994
  • 10853
  • 9121
  • 8524
  • 7166
  • 6403
  • 6248
  • 6192
  • 6063
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
201

Evaluation of a Benchmark Suite Exposing Android System Complexities Using Region-Based Caching

Unknown Date (has links)
The computer architecture community relies on standard benchmark suites like MiBench, NAS, PARSEC, SPEC CPU2006 (SPEC)®, and SPLASH to study different hardware designs, but such suites are insufficient for evaluating mobile platforms like Android. Even suites that were developed for embedded systems cannot be used to gain an understanding of Android device/system interaction because they do not exercise key components of the software stack. Although based on a conventional Linux ® kernel, Android includes native libraries, a virtual machine runtime, and an application framework with multiple components for managing resources. All these interact in complex ways to support Android applications. C programs running on Linux have a relatively simple virtual memory organization, and most memory references come from the application code. In contrast, Android has a much more complex virtual memory organization (due to its multiple APIs and numerous shared libraries), and most memory references come from the Android software stack. The complexity of Android's execution environment provides opportunities for computer architects to better support the execution characteristics, structures, and resource requirements of the Android software stack and opportunities for software developers to optimize their applications for this rich environment. To help the community to exploit these opportunities, we introduce Agave, an open-source benchmark suite designed to expose the complex interactions between components of the Android software stack. / A Dissertation submitted to the Department of Computer Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy. / Fall Semester 2016. / November 14, 2016. / Android, Based, Benchmark, Caching, Region / Includes bibliographical references. / Gary Tyson, Professor Directing Dissertation; Linda DeBrunner, University Representative; David Whalley, Committee Member; Xin Yuan, Committee Member.
202

The Dynamic Mapping Architecture

Royko, Thomas Charles January 2021 (has links)
No description available.
203

Continuous Human Activity Tracking over a Large Area with Multiple Kinect Sensors

Hans, Akshat C. 31 August 2018 (has links)
No description available.
204

Internet of Wearable Things: Cooperative Sensing and Computing for Hand Gesture Recognition

Zhang, Xiaoliang 01 February 2019 (has links)
No description available.
205

Accelerating Analytical Query Processing with Data Placement Conscious Optimization and RDMA-aware Query Execution

Liu, Feilong January 2018 (has links)
No description available.
206

Designing High Performance Scheduling Policies in Multi-channel and Multi-antenna Networks

Qian, Zhenzhi 25 June 2019 (has links)
No description available.
207

Approximation algorithms for routing and related problems on directed minor-free graphs

Salmasi, Ario 02 October 2019 (has links)
No description available.
208

Sensing and Anti-sensing with Wireless Communication Signal

Zhang, Ouyang 17 October 2019 (has links)
No description available.
209

Enabling Efficient Parallelism for Applications with Dependences and Irregular Memory Accesses

Jiang, Peng 06 November 2019 (has links)
No description available.
210

Predicting Performance of Parallel Analytics and Irregular Computations

Zhu, Gangyi 23 October 2019 (has links)
No description available.

Page generated in 0.3172 seconds