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Bootstomp: on the Security of Bootloaders in Mobile Devices
BootStomp: On the Security of Bootloaders in Mobile Devices Nilo Redini, Aravind Machiry, Dipanjan Das, Yanick Fratantonio, Antonio Bianchi, Eric Gustafson, Yan Shoshitaishvili, Christopher Kruegel, and Giovanni Vigna, UC Santa Barbara https://www.usenix.org/conference/usenixsecurity17/technical-sessions/presentation/redini This paper is included in the Proceedings of the 26th USENIX Security Symposium August 16–18, 2017 • Vancouver, BC, Canada ISBN 978-1-931971-40-9 Open access to the Proceedings of the 26th USENIX Security Symposium is sponsored by USENIX BootStomp: On the Security of Bootloaders in Mobile Devices Nilo Redini, Aravind Machiry, Dipanjan Das, Yanick Fratantonio, Antonio Bianchi, Eric Gustafson, Yan Shoshitaishvili, Christopher Kruegel, and Giovanni Vigna fnredini, machiry, dipanjan, yanick, antoniob, edg, yans, chris, [email protected] University of California, Santa Barbara Abstract by proposing simple mitigation steps that can be im- plemented by manufacturers to safeguard the bootloader Modern mobile bootloaders play an important role in and OS from all of the discovered attacks, using already- both the function and the security of the device. They deployed hardware features. help ensure the Chain of Trust (CoT), where each stage of the boot process verifies the integrity and origin of 1 Introduction the following stage before executing it. This process, in theory, should be immune even to attackers gaining With the critical importance of the integrity of today’s full control over the operating system, and should pre- mobile and embedded devices, vendors have imple- vent persistent compromise of a device’s CoT. However, mented a string of inter-dependent mechanisms aimed at not only do these bootloaders necessarily need to take removing the possibility of persistent compromise from untrusted input from an attacker in control of the OS in the device. -
GPU Developments 2018
GPU Developments 2018 2018 GPU Developments 2018 © Copyright Jon Peddie Research 2019. All rights reserved. Reproduction in whole or in part is prohibited without written permission from Jon Peddie Research. This report is the property of Jon Peddie Research (JPR) and made available to a restricted number of clients only upon these terms and conditions. Agreement not to copy or disclose. This report and all future reports or other materials provided by JPR pursuant to this subscription (collectively, “Reports”) are protected by: (i) federal copyright, pursuant to the Copyright Act of 1976; and (ii) the nondisclosure provisions set forth immediately following. License, exclusive use, and agreement not to disclose. Reports are the trade secret property exclusively of JPR and are made available to a restricted number of clients, for their exclusive use and only upon the following terms and conditions. JPR grants site-wide license to read and utilize the information in the Reports, exclusively to the initial subscriber to the Reports, its subsidiaries, divisions, and employees (collectively, “Subscriber”). The Reports shall, at all times, be treated by Subscriber as proprietary and confidential documents, for internal use only. Subscriber agrees that it will not reproduce for or share any of the material in the Reports (“Material”) with any entity or individual other than Subscriber (“Shared Third Party”) (collectively, “Share” or “Sharing”), without the advance written permission of JPR. Subscriber shall be liable for any breach of this agreement and shall be subject to cancellation of its subscription to Reports. Without limiting this liability, Subscriber shall be liable for any damages suffered by JPR as a result of any Sharing of any Material, without advance written permission of JPR. -
Streaming Integrated Amplifier User’S Manual U S E’ S M an U a L
OmniaOmnia A300 Streaming Integrated Amplifier User’s Manual U S E’ S M AN U A L Table of Contents FCC NOTICE - DECLARATION OF CONFORMITY INFORMATION .................................................................... 2 EU DECLARATION OF CONFORMITY ........................................................................................................... 3 SAFETY INSTRUCTIONS ............................................................................................................................. 4 WHAT’S IN THE BOX .................................................................................................................................. 7 QUICK SETUP GUIDE .............................................................................................................................. 8 WIRELESS AUTO SETUP ............................................................................................................................. 9 CONTROLLING MULTIPLE A300 AND RE-STREAMING ........................................................................ 14 WIRELESS MANUAL SETUP ................................................................................................................. 16 INTRODUCTION ................................................................................................................................... 17 TECHNICAL HIGHLIGHTS ......................................................................................................................... 17 LISTENING OPTIMIZATION ..................................................................................................................... -
Mediatek Linkit™ Development Platform for RTOS Get Started Guide
MediaTek LinkIt™ Development Platform for RTOS Get Started Guide Version: 3.0 Release date: 30 June 2016 © 2015 - 2016 MediaTek Inc. This document contains information that is proprietary to MediaTek Inc. (“MediaTek”) and/or its licensor(s). MediaTek cannot grant you permission for any material that is owned by third parties. You may only use or reproduce this document if you have agreed to and been bound by the applicable license agreement with MediaTek (“License Agreement”) and been granted explicit permission within the License Agreement (“Permitted User”). If you are not a Permitted User, please cease any access or use of this document immediately. Any unauthorized use, reproduction or disclosure of this document in whole or in part is strictly prohibited. THIS DOCUMENT IS PROVIDED ON AN “AS-IS” BASIS ONLY. MEDIATEK EXPRESSLY DISCLAIMS ANY AND ALL WARRANTIES OF ANY KIND AND SHALL IN NO EVENT BE LIABLE FOR ANY CLAIMS RELATING TO OR ARISING OUT OF THIS DOCUMENT OR ANY USE OR INABILITY TO USE THEREOF. Specifications contained herein are subject to change without notice. MediaTek LinkIt™ Development Platform for RTOS Get Started Guide Document Revision History Revision Date Description 1.0 24 March 2016 Initial version. 2.0 17 May 2016 Move the contents relative to flash, HDK, and build comments to corresponding documents. Add the support of Keil 3.0 30 June 2016 Add the support of IAR. Refine the architecture and provide more information on the SDK usage. © 2015 - 2016 MediaTek Inc. Page i of v This document contains information that is proprietary to MediaTek Inc. -
Performance Analysis and Optimization Opportunities for NVIDIA Automotive Gpus
Performance Analysis and Optimization Opportunities for NVIDIA Automotive GPUs Hamid Tabani∗, Fabio Mazzocchetti∗y, Pedro Benedicte∗y, Jaume Abella∗ and Francisco J. Cazorla∗ ∗ Barcelona Supercomputing Center y Universitat Politecnica` de Catalunya Abstract—Advanced Driver Assistance Systems (ADAS) and products such as Renesas R-Car H3 [1], NVIDIA Jetson Autonomous Driving (AD) bring unprecedented performance TX2 [20] and NVIDIA Jetson Xavier [35], [27] have already requirements for automotive systems. Graphic Processing Unit reached the market building upon GPU technology inherited (GPU) based platforms have been deployed with the aim of meeting these requirements, being NVIDIA Jetson TX2 and from the high-performance domain. Automotive GPUs have its high-performance successor, NVIDIA AGX Xavier, relevant inherited designs devised for the high-performance domain representatives. However, to what extent high-performance GPU with the aim of reducing costs in the design, verification and configurations are appropriate for ADAS and AD workloads validation process for chip manufacturers. remains as an open question. Unfortunately, reusability of high-performance hardware This paper analyzes this concern and provides valuable does not consider GPUs efficiency in the automotive domain insights on this question by modeling two recent automotive NVIDIA GPU-based platforms, namely TX2 and AGX Xavier. In and, to the best of our knowledge, the design space for GPUs, particular, our work assesses their microarchitectural parameters where resources are sized with the aim of optimizing specific against relevant benchmarks, identifying GPU setups delivering goals such as performance, has not been yet thoroughly increased performance within a similar cost envelope, or decreas- performed for the automotive domain. ing hardware costs while preserving original performance levels. -
Mediatek Inc. 2019 Annual General Shareholders' Meeting Minutes
MediaTek Inc. 2019 Annual General Shareholders’ Meeting Minutes Time: 9:00 a.m., June 14, 2019 Place: International Convention Center, MediaTek Inc. (No. 1, Dusing 1st Road, Hsinchu Science Park, Hsinchu City, Taiwan R.O.C.) The Number of Shares of Attendance: Attending shareholders and proxy represented 1,305,281,888 shares (including 1,066,881,115 shares which attended through electronic voting) accounting for 82.30% of 1,585,899,498 shares, the Company’s total outstanding shares (deducting non-voting shares as required in Article 179 of the Company Act) Directors Present: Ming-Kai Tsai, Rick Tsai, Ching-Jiang Hsieh, Wayne Liang, Cheng-Yaw Sun, Peng-Heng Chang, Chung-Yu Wu Chairman: Mr. Ming-Kai Tsai Recorder: Ms. Emma Chang Call the Meeting to Order: The aggregate shareholding of the shareholders present constituted a quorum. The Chairman called the meeting to order. 1. Chairman’s Remarks: Omitted. 2. Reporting Items: Report Item (1) Subject: MediaTek’s 2018 business report. Explanatory Note: MediaTek’s 2018 business report is attached hereto as Attachment 1. (Noted) Report Item (2) Subject: Audit Committee’s review report on the 2018 financial statements. Explanatory Note: 2018 Audit Committee’s review report is attached hereto as Attachment 2. (Noted) Report Item (3) Subject: Report on 2018 employees’ compensation and remuneration to directors. Explanatory Note: (1). According to Article 24 of the Company's Articles of Incorporation, if there is any profit for a specific fiscal year, the Company shall allocate no less than 1% of the profit as employees’ compensation and shall allocate at a maximum of 0.5% of the profit as remuneration to directors, provided that the Company’s accumulated losses shall have been covered in advance. -
NVIDIA Launches Tegra X1 Mobile Super Chip
NVIDIA Launches Tegra X1 Mobile Super Chip Maxwell GPU Architecture Delivers First Teraflops Mobile Processor, Powering Deep Learning and Computer Vision Applications NVIDIA today unveiled Tegra® X1, its next-generation mobile super chip with over one teraflops of processing power – delivering capabilities that open the door to unprecedented graphics and sophisticated deep learning and computer vision applications. Tegra X1 is built on the same NVIDIA Maxwell™ GPU architecture rolled out only months ago for the world's top-performing gaming graphics card, the GeForce® GTX 980. The 256-core Tegra X1 provides twice the performance of its predecessor, the Tegra K1, which is based on the previous-generation Kepler™ architecture and debuted at last year's Consumer Electronics Show. Tegra processors are built for embedded products, mobile devices, autonomous machines and automotive applications. Tegra X1 will begin appearing in the first half of the year. It will be featured in the newly announced NVIDIA DRIVE™ car computers. DRIVE PX is an auto-pilot computing platform that can process video from up to 12 onboard cameras to run capabilities providing Surround-Vision, for a seamless 360-degree view around the car, and Auto-Valet, for true self-parking. DRIVE CX is a complete cockpit platform designed to power the advanced graphics required across the increasing number of screens used for digital clusters, infotainment, head-up displays, virtual mirrors and rear-seat entertainment. "We see a future of autonomous cars, robots and drones that see and learn, with seeming intelligence that is hard to imagine," said Jen-Hsun Huang, CEO and co-founder, NVIDIA. -
– Amlogic S905X2 Chipset – Armv8-A Architecture – ARM G31
NV-720 series IPTV Set-Top Boxes Data Sheet Integrated Networking Solutions – Amlogic S905X2 chipset – ARMv8-A architecture – ARM G31 MP2 graphic accelerator – 2D/3D accelerators, support for OpenGL 3.2 – OS Android 9 – App store – Support for widely used Middleware – Android API, SDK – H.265 – 4Kp60 decoding – Wi-Fi 802.11a/b/g/n/ac – HDMI 2.1 NV-720 IPTV set-top boxes on Android ensure a new Peer-to-Peer TV level of service provision. NV-720 series set-top boxes support real-time NV-720 is an excellent way to promote digital television playback of media files via DC++ protocol without a services and to attract new customers. PC or files preloading to a local disk. There is an opportunity of downloaded files queue creation, Android platform background downloading and organization of an NV-711 Android allows the creation of a single universal illustrated page (catalogue) for media content. platform for access to services including AndroidTV interface. Basic services – HD/UHD IPTV Customized app store creation – OTT The open platform and development tools (SDK, API) – VoD make it possible to create new operator services. – Media Player (files playback from external storage media and a local network) Hardware – Electronic program guide (EPG) Quad-core Amlogic media processor supports a wide – Support for cloud services range of audio and video formats. – Online sources: YouTube, Internet radio, etc. – Provider’s app store Up-to-date Wi-Fi technologies – Support for HLS NV-720-WB set-top boxes support up-to-date Wi-Fi – Peer-to-Peer TV (streaming via DC++) standards: 802.11a/b/g/n/ас. -
Co-Optimizing Performance and Memory Footprint Via Integrated CPU/GPU Memory Management, an Implementation on Autonomous Driving Platform
Co-Optimizing Performance and Memory Footprint Via Integrated CPU/GPU Memory Management, an Implementation on Autonomous Driving Platform Soroush Bateni*, Zhendong Wang*, Yuankun Zhu, Yang Hu, and Cong Liu The University of Texas at Dallas Abstract—Cutting-edge embedded system applications, such as launches the OpenVINO toolkit for the edge-based deep self-driving cars and unmanned drone software, are reliant on learning inference on its integrated HD GPUs [4]. integrated CPU/GPU platforms for their DNNs-driven workload, Despite the advantages in SWaP features presented by the such as perception and other highly parallel components. In this work, we set out to explore the hidden performance im- integrated CPU/GPU architecture, our community still lacks plication of GPU memory management methods of integrated an in-depth understanding of the architectural and system CPU/GPU architecture. Through a series of experiments on behaviors of integrated GPU when emerging autonomous and micro-benchmarks and real-world workloads, we find that the edge intelligence workloads are executed, particularly in multi- performance under different memory management methods may tasking fashion. Specifically, in this paper we set out to explore vary according to application characteristics. Based on this observation, we develop a performance model that can predict the performance implications exposed by various GPU memory system overhead for each memory management method based management (MM) methods of the integrated CPU/GPU on application characteristics. Guided by the performance model, architecture. The reason we focus on the performance impacts we further propose a runtime scheduler. By conducting per-task of GPU MM methods are two-fold. -
A Low-Cost Deep Neural Network-Based Autonomous Car
DeepPicar: A Low-cost Deep Neural Network-based Autonomous Car Michael G. Bechtely, Elise McEllhineyy, Minje Kim?, Heechul Yuny y University of Kansas, USA. fmbechtel, elisemmc, [email protected] ? Indiana University, USA. [email protected] Abstract—We present DeepPicar, a low-cost deep neural net- task may be directly linked to the safety of the vehicle. This work based autonomous car platform. DeepPicar is a small scale requires a high computing capacity as well as the means to replication of a real self-driving car called DAVE-2 by NVIDIA. guaranteeing the timings. On the other hand, the computing DAVE-2 uses a deep convolutional neural network (CNN), which takes images from a front-facing camera as input and produces hardware platform must also satisfy cost, size, weight, and car steering angles as output. DeepPicar uses the same net- power constraints, which require a highly efficient computing work architecture—9 layers, 27 million connections and 250K platform. These two conflicting requirements complicate the parameters—and can drive itself in real-time using a web camera platform selection process as observed in [25]. and a Raspberry Pi 3 quad-core platform. Using DeepPicar, we To understand what kind of computing hardware is needed analyze the Pi 3’s computing capabilities to support end-to-end deep learning based real-time control of autonomous vehicles. for AI workloads, we need a testbed and realistic workloads. We also systematically compare other contemporary embedded While using a real car-based testbed would be most ideal, it computing platforms using the DeepPicar’s CNN-based real-time is not only highly expensive, but also poses serious safety control workload. -
Certain Semiconductor Devices and Consumer Audiovisual Products Containing the Same That Infringe U.S
UNITED STATES INTERNATIONAL TRADE COMMISSION Washington, D.C. In the Matter of CERTAIN SEMICONDUCTOR Investigation No. 337-TA-1047 DEVICES AND CONSUMER AUDIOVISUAL PRODUCTS CONTAINING THE SAME NOTICE OF COMMISSION DETERMINATION NOT TO REVIEW AN INITIAL DETERMINATION TERMINATING THE INVESTIGATION AS TO ONE RESPONDENT GROUP AGENCY: U.S. International Trade Commission. ACTION: Notice. SUMMARY: Notice is hereby given that the U.S. International Trade Commission has determined not to review an initial determination (“ID”) (Order No. 35) issued by the presiding administrative law judge (“ALJ”). FOR FURTHER INFORMATION CONTACT: Robert Needham, Office of the General Counsel, U.S. International Trade Commission, 500 E Street, SW., Washington, D.C. 20436, telephone (202) 708-5468. Copies of non-confidential documents filed in connection with this investigation are or will be available for inspection during official business hours (8:45 a.m. to 5:15 p.m.) in the Office of the Secretary, U.S. International Trade Commission, 500 E Street, SW., Washington, D.C. 20436, telephone (202) 205- 2000. General information concerning the Commission may also be obtained by accessing its Internet server (https://www.usitc.gov). The public record for this investigation may be viewed on the Commission's electronic docket (EDIS) at https://edis.usitc.gov. Hearing-impaired persons are advised that information on this matter can be obtained by contacting the Commission’s TDD terminal on (202) 205- 1810. SUPPLEMENTARY INFORMATION: The Commission instituted this investigation on April 12, 2017, based on a complaint filed by Broadcom Corporation (“Broadcom”) of Irvine, California. 82 FR 17688. The complaint alleges violations of section 337 of the Tariff Act of 1930, as amended, 19 U.S.C. -
Last Updated 07/12/16 2017 Final Tier Assignment, Alphabetic by Manufacturer Below Is the 2017 Final Tier Assignment Schedule Fo
Last Updated 07/12/16 2017 Final Tier Assignment, Alphabetic by Manufacturer Below is the 2017 Final Tier Assignment Schedule for Washington’s Electronic Product Recycling Program. The purpose of the 2017 Tier Assignment is to determine manufacturer fees owed to the Department of Ecology. These fees are used to cover Ecology’s administrative costs for implementing the E-Cycle Washington program. Ecology identified the manufacturers listed below as the brand owners of electronic products covered by this program (computers, monitors, laptops, televisions, portable DVD players, tablets, and e-Readers). Is Your Registration Up to Date? • Manufacturers who own additional brands of covered electronic products not currently registered must add those brands to their registration. • Brand owners of covered electronic products that are not on this list must register as a new participant. • Brand association list. If you have questions, please contact Christine Haun at 360-407-6107 or [email protected]. 2017 Tier Manufacturer 6 3M Touch Systems 4 3MD Inc. 5 4th Dimension Computer 6 Abacus Office Machines 6 ACC Tech 2 Acer America Corp 6 ADT LLC dba ADT Security Services 6 Afunta LLC 6 AMA Computer Services, LLC 3 Amazon Fulfillment Services, Inc. 6 AMDOE, LLC 6 Amelia World Corp d/b/a LINSAY 5 American Future Tech Corp dba iBuypower 6 American Pumpkins, Inc. 6 American Sunrex Corporation 6 Andteck 6 Angel Computer Systems Inc 2 Apple 6 Associated Computer Specialists 2 Asus Computer International 6 Atron Vision 6 AWA Technology Inc. 6 Axess Products Corporation 6 Azend Group Corp 6 Azpen Innovation, Inc.