Matt Spisak Recon 2016, Montreal RECON 2016
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An Emerging Architecture in Smart Phones
International Journal of Electronic Engineering and Computer Science Vol. 3, No. 2, 2018, pp. 29-38 http://www.aiscience.org/journal/ijeecs ARM Processor Architecture: An Emerging Architecture in Smart Phones Naseer Ahmad, Muhammad Waqas Boota * Department of Computer Science, Virtual University of Pakistan, Lahore, Pakistan Abstract ARM is a 32-bit RISC processor architecture. It is develop and licenses by British company ARM holdings. ARM holding does not manufacture and sell the CPU devices. ARM holding only licenses the processor architecture to interested parties. There are two main types of licences implementation licenses and architecture licenses. ARM processors have a unique combination of feature such as ARM core is very simple as compare to general purpose processors. ARM chip has several peripheral controller, a digital signal processor and ARM core. ARM processor consumes less power but provide the high performance. Now a day, ARM Cortex series is very popular in Smartphone devices. We will also see the important characteristics of cortex series. We discuss the ARM processor and system on a chip (SOC) which includes the Qualcomm, Snapdragon, nVidia Tegra, and Apple system on chips. In this paper, we discuss the features of ARM processor and Intel atom processor and see which processor is best. Finally, we will discuss the future of ARM processor in Smartphone devices. Keywords RISC, ISA, ARM Core, System on a Chip (SoC) Received: May 6, 2018 / Accepted: June 15, 2018 / Published online: July 26, 2018 @ 2018 The Authors. Published by American Institute of Science. This Open Access article is under the CC BY license. -
NVIDIA Tegra 4 Family CPU Architecture 4-PLUS-1 Quad Core
Whitepaper NVIDIA Tegra 4 Family CPU Architecture 4-PLUS-1 Quad core 1 Table of Contents ...................................................................................................................................................................... 1 Introduction .............................................................................................................................................. 3 NVIDIA Tegra 4 Family of Mobile Processors ............................................................................................ 3 Benchmarking CPU Performance .............................................................................................................. 4 Tegra 4 Family CPUs Architected for High Performance and Power Efficiency ......................................... 6 Wider Issue Execution Units for Higher Throughput ............................................................................ 6 Better Memory Level Parallelism from a Larger Instruction Window for Out-of-Order Execution ...... 7 Fast Load-To-Use Logic allows larger L1 Data Cache ............................................................................. 8 Enhanced branch prediction for higher efficiency .............................................................................. 10 Advanced Prefetcher for higher MLP and lower latency .................................................................... 10 Large Unified L2 Cache ....................................................................................................................... -
Hardware-Assisted Rootkits: Abusing Performance Counters on the ARM and X86 Architectures
Hardware-Assisted Rootkits: Abusing Performance Counters on the ARM and x86 Architectures Matt Spisak Endgame, Inc. [email protected] Abstract the OS. With KPP in place, attackers are often forced to move malicious code to less privileged user-mode, to ele- In this paper, a novel hardware-assisted rootkit is intro- vate privileges enabling a hypervisor or TrustZone based duced, which leverages the performance monitoring unit rootkit, or to become more creative in their approach to (PMU) of a CPU. By configuring hardware performance achieving a kernel mode rootkit. counters to count specific architectural events, this re- Early advances in rootkit design focused on low-level search effort proves it is possible to transparently trap hooks to system calls and interrupts within the kernel. system calls and other interrupts driven entirely by the With the introduction of hardware virtualization exten- PMU. This offers an attacker the opportunity to redirect sions, hypervisor based rootkits became a popular area control flow to malicious code without requiring modifi- of study allowing malicious code to run underneath a cations to a kernel image. guest operating system [4, 5]. Another class of OS ag- The approach is demonstrated as a kernel-mode nostic rootkits also emerged that run in System Manage- rootkit on both the ARM and Intel x86-64 architectures ment Mode (SMM) on x86 [6] or within ARM Trust- that is capable of intercepting system calls while evad- Zone [7]. The latter two categories, which leverage vir- ing current kernel patch protection implementations such tualization extensions, SMM on x86, and security exten- as PatchGuard. -
ARM Debugger
ARM Debugger TRACE32 Online Help TRACE32 Directory TRACE32 Index TRACE32 Documents ...................................................................................................................... ICD In-Circuit Debugger ................................................................................................................ Processor Architecture Manuals .............................................................................................. ARM/CORTEX/XSCALE ........................................................................................................... ARM Debugger ..................................................................................................................... 1 History ................................................................................................................................ 7 Warning .............................................................................................................................. 8 Introduction ....................................................................................................................... 9 Brief Overview of Documents for New Users 9 Demo and Start-up Scripts 10 Quick Start of the JTAG Debugger .................................................................................. 12 FAQ ..................................................................................................................................... 13 Troubleshooting ............................................................................................................... -
A Tour of the ARM Architecture and Its Linux Support
Linux Conf Australia 2017 A tour of the ARM architecture and its Linux support Thomas Petazzoni Bootlin [email protected] - Kernel, drivers and embedded Linux - Development, consulting, training and support - https://bootlin.com 1/1 I Since 2012: Linux kernel contributor, adding support for Marvell ARM processors I Core contributor to the Buildroot project, an embedded Linux build system I From Toulouse, France Thomas Petazzoni I Thomas Petazzoni I CTO and Embedded Linux engineer at Bootlin I Embedded Linux expertise I Development, consulting and training I Strong open-source focus I Linux kernel contributors, ARM SoC support, kernel maintainers embedded Linux and kernel engineering - Kernel, drivers and embedded Linux - Development, consulting, training and support - https://bootlin.com 2/1 I Core contributor to the Buildroot project, an embedded Linux build system I From Toulouse, France Thomas Petazzoni I Thomas Petazzoni I CTO and Embedded Linux engineer at Bootlin I Embedded Linux expertise I Development, consulting and training I Strong open-source focus I Linux kernel contributors, ARM SoC support, kernel maintainers I Since 2012: Linux kernel contributor, adding support for Marvell ARM processors - Kernel, drivers and embedded Linux - Development, consulting, training and support - https://bootlin.com 2/1 I From Toulouse, France Thomas Petazzoni I Thomas Petazzoni I CTO and Embedded Linux engineer at Bootlin I Embedded Linux expertise I Development, consulting and training I Strong open-source focus I Linux kernel contributors, -
Modem Product Portfolio
Blogger Workshop Benchmark Summary: MDP Tablet Featuring APQ8064 Quad-Core © 2012 QUALCOMM Incorporated. All rights reserved. 1 Executive Overview . On July 24th, 2012, 30 bloggers (15 International, 15 U.S) descended into San Francisco, CA to take part in a blogger’s workshop where they spent unsupervised time benchmarking and testing our latest tablet MDP equipped with the APQ8064, otherwise known as the Snapdragon S4 Pro. The tone of coverage overall was extremely positive. Bloggers who attended the workshop raved about the performance of the quad-core devices and the potential benefits for developers. The graphics garnered particular acclaim, especially in comparison to competitor’s quad-core devices. The articles from the workshop attendees spurred a second wave of global coverage, especially in China, that took note of their reviews as well as the availability of the MDP. Below is a compilation of benchmark data pulled from various third party sources, including Anandtech, TheVerge, SlashGear, and Android Community. This benchmark data reflects performance across multiple vectors in the Snapdragon S4 Pro, including CPU, GPU and browsing. In the same deck, commercial devices featuring our dual core Snapdragon S4 processor has been updated to reflect data from the Samsung Galaxy S3 (MSM8960). © 2012 QUALCOMM Incorporated. All rights reserved. 2 Snapdragon S4 Pro APQ8064 MDP HEADLINE: “Qualcomm Snapdragon S4 Pro quad-core developer tablet shows off stunning benchmark performance” “It's fast, handily eclipsing the Samsung Galaxy SIII’s Exynos 4 Quad, the HTC One X’s Tegra 3, and Qualcomm's own Snapdragon S4 on a spate of synthetic benchmarks.” – Nate Ralph, TheVerge Source: TheVerge by Nate Ralph 7/24/2012 http://www.theverge.com/2012/7/24/3185016/qualcomm-snapdragon-s4-pro-APQ8064 © 2012 QUALCOMM Incorporated. -
Arm-Debugger-Lauterbach-75570.Pdf
ARM Debugger TRACE32 Online Help TRACE32 Directory TRACE32 Index TRACE32 Documents ...................................................................................................................... ICD In-Circuit Debugger ................................................................................................................ Processor Architecture Manuals .............................................................................................. ARM/CORTEX/XSCALE ........................................................................................................... ARM Debugger ..................................................................................................................... 1 Warning .............................................................................................................................. 8 Introduction ....................................................................................................................... 9 Brief Overview of Documents for New Users 9 Demo and Start-up Scripts 10 Quick Start of the JTAG Debugger .................................................................................. 12 Troubleshooting ................................................................................................................ 14 Communication between Debugger and Processor can not be established 14 FAQ ..................................................................................................................................... 15 ARM 15 Trace Extensions .............................................................................................................. -
Droidcluster: Towards Smartphone Cluster Computing the Streets Are Paved with Potential Computer Clusters
DroidCluster: Towards Smartphone Cluster Computing The Streets are Paved with Potential Computer Clusters Sebastian Schildt, Felix B¨usching,Lars Wolf PhoneCom 2012 Introduction The Cluster Implications Opportunities Once upon a time... In the beginning of 2011 we bought 6 medium class Android Smartphones for a programming lab. LG P500, Android 2.2, 600 MHz Qualcomm MSM7227, 512 MiB RAM Sebastian Schildt j DroidCluster: Towards Smartphone Cluster Computing j 2 We should build a cluster out of it! Sounds like a reasonable idea! Introduction The Cluster Implications Opportunities The idea... Sebastian Schildt j DroidCluster: Towards Smartphone Cluster Computing j 3 Sounds like a reasonable idea! Introduction The Cluster Implications Opportunities The idea... We should build a cluster out of it! Sebastian Schildt j DroidCluster: Towards Smartphone Cluster Computing j 3 Introduction The Cluster Implications Opportunities The idea... We should build a cluster out of it! Sounds like a reasonable idea! Sebastian Schildt j DroidCluster: Towards Smartphone Cluster Computing j 3 Introduction The Cluster Implications Opportunities Architecture USB-Connection (a) Wireless Access Point WiFi-Connection (b) Android #1 Control PC MPI Master 2 3 4 5 6 MPI Slaves Sebastian Schildt j DroidCluster: Towards Smartphone Cluster Computing j 4 Introduction The Cluster Implications Opportunities Software Full ARM Debian installation alongside the Android OS (chroot) MPI-based Linpack benchmark Connectivity through WiFi or USB reverse-tethering Control PC only used -
ARM NEON Assembly Optimization Dae-Hwan Kim Department of Computer and Information, Suwon Science College, 288 Seja-Ro, Jeongnam-Myun, Hwaseong-Si, Gyeonggi-Do, Rep
Journal of Multidisciplinary Engineering Science and Technology (JMEST) ISSN: 2458-9403 Vol. 3 Issue 4, April - 2016 ARM NEON Assembly Optimization Dae-Hwan Kim Department of Computer and Information, Suwon Science College, 288 Seja-ro, Jeongnam-myun, Hwaseong-si, Gyeonggi-do, Rep. of Korea [email protected] Abstract—ARM is one of the most widely used The ARMv8 architecture [3, 4] introduces a 64-bit 32-bit processors, which is embedded in architecture, named AArch64, and a new A64 smartphones, tablets, and various electronic instruction set to the existing instruction set to support devices. The ARM NEON is the SIMD engine inside the 64-bit operation and the virtual addressing. ARM core which accelerates multimedia and In this paper, various assembly software signal processing algorithms. NEON is widely optimization techniques are proposed for the ARM incorporated in the recent ARM processors for NEON architecture. Practical example code is given to smartphones and tablets. In this paper, various the optimization technique, whose performance is assembly level software optimizations are analyzed, compared to the original code. provided such as instruction scheduling, instruction selection, and loop unrolling for the The rest of this paper is organized as follows. NEON architecture. The proposed techniques are Section II shows the overview of the assembly expected to be applied directly in the software optimizations, and Section III presents each technique development for the ARM NEON processors. in detail with an example. Conclusions are presented in Section IV. Keywords—ARM; NEON; embedded processor; software optimization; assembly II. ASSEMBLY OPTIMIZATION OVERVIEW NEON is the SIMD (Single Instruction Multiple Data) I. -
1 in the United States District Court for the Northern
Case: 1:18-cv-06255 Document #: 1 Filed: 09/13/18 Page 1 of 19 PageID #:1 IN THE UNITED STATES DISTRICT COURT FOR THE NORTHERN DISTRICT OF ILLINOIS EASTERN DIVISION COMPLEX MEMORY, LLC, Plaintiff Civil Action No.: 1:18-cv-6255 v. PATENT CASE MOTOROLA MOBILITY LLC Jury Trial Demanded Defendant COMPLAINT FOR PATENT INFRINGEMENT Plaintiff Complex Memory, LLC (“Complex Memory”), by way of this Complaint against Defendant Motorola Mobility LLC (“Motorola” or “Defendant”), alleges as follows: PARTIES 1. Plaintiff Complex Memory is a limited liability company organized and existing under the laws of the State of Texas, having its principal place of business at 17330 Preston Road, Suite 200D, Dallas, Texas 75252. 2. On information and belief, Defendant Motorola is a Delaware limited liability company headquartered at 222 W. Merchandise Mart Plaza, Chicago, IL 60654. JURISDICTION AND VENUE 3. This is an action under the patent laws of the United States, 35 U.S.C. §§ 1, et seq., for infringement by Motorola of claims of U.S. Patent Nos. 5,890,195; 5,963,481; 6,658,576; 6,968,469; and 7,730,330 (“the Patents-in-Suit”). 4. This Court has subject matter jurisdiction pursuant to 28 U.S.C. §§ 1331 and 1338(a). 5. Motorola is subject to personal jurisdiction of this Court because, inter alia, on 1 Case: 1:18-cv-06255 Document #: 1 Filed: 09/13/18 Page 2 of 19 PageID #:2 information and belief, (i) Motorola is registered to transact business in the State of Illinois; (ii) Motorola conducts business in the State of Illinois and maintains a facility and employees within the State of Illinois; and (iii) Motorola has committed and continues to commit acts of patent infringement in the State of Illinois, including by making, using, offering to sell, and/or selling accused products and services in the State of Illinois, and/or importing accused products and services into the State of Illinois. -
Cache Attacks on ARM
Moritz Lipp Cache Attacks on ARM Master thesis Graz, University Of Technology NOTICE If you want to cite this work based on last-level cache attacks on ARM, please cite the following research paper instead: •L ipp, Moritz ; Gruss, Daniel ; Spreitzer, Raphael ; Maurice, Clementine´ ;Mangard, Stefan: ARMageddon: Cache Attacks on Mobile De- vices. In: 25th USENIX Security Symposium (USENIX Security 16). Austin, TX : USENIX Association, August 2016. – ISBN 978–1–931971– 32–4, 549–564 If you want to cite this work in respect to rowhammer on ARM-based devices, please cite the following publication instead: •V een, Victor van d. ; Fratantonio, Yanick ; Lindorfer, Martina ; Gruss, Daniel ; Maurice, Clementine´ ; Vigna, Giovanni ; Bos, Her- bert ; Razavi, Kaveh ; Giuffrida, Christiano: Drammer : Determinis- tic Rowhammer Attacks on Commodity Mobile Platforms. In: ACM Conference on Computer and Communications Security – CCS, 2016 Contents 1 Introduction 1 1.1 Motivation . .3 1.2 Key Challenges and Results . .4 1.3 Contributions . .5 1.4 Test devices . .6 1.5 Outline . .7 2 Background 9 2.1 CPU caches . .9 2.2 Cache coherence . 18 2.3 Shared memory . 29 2.4 Cache Attacks . 31 2.5 DRAM . 39 3 Attack primitives 43 3.1 Timing Measurements . 43 3.2 Cache Eviction . 47 3.3 Defeating the Cache-Organization . 53 4 Attack Case Studies 57 4.1 High Performance Covert-Channels . 58 4.2 Spying on User input . 62 4.3 Attacks on Cryptographic Algorithms . 69 4.4 Rowhammer on ARM . 75 5 Countermeasures 79 6 Conclusion 81 i List of tables . 83 List of figures . 86 List of acronyms . -
High Performance, Ultra-Low Power Streaming Systems
TECHNICAL UNIVERSITY OF CATALONIA School of Informatics Master on Computer Architecture, Networks and Systems Master Thesis High Performance, Ultra-Low Power Streaming Systems Student: Jos´eMar´ıaArnau Advisor: Joan-Manuel Parcerisa Advisor: Polychronis Xekalakis Advisor: Antonio Gonz´alez Date: September 20, 2011 2 Abstract Smartphones are emerging as one of the fastest growing markets, with new devices and im- provements in their operating systems taking place every few months. The design of a CPU/GPU for such a mobile devices is challenging due to the users demands for a truly mobile computing experience, including highly responsive user interfaces, uncompromised web browsing performance or visually compelling gaming experiences, and the power constrains due to the limited capacity of the battery. In the last years, the power demand of these mobile devices has increased much faster than the battery improvements. Our key ambition is to design a CPU/GPU for such a system, trying to minimize the power consumed, while also achieving the highest performance possible. We first analyze commercial Android workloads and establish that the most demanding applications in terms of performance are, as expected, games. We show that because these systems are based on OpenGL ES, the vast majority of the time the CPU is idle. In fact, we find that the GPU is much more active than the CPU and that the major performance limitation for these systems is the use of memory by the GPU. We thus focus on the GPU and more specifically on its memory behavior. We show that for most of the caches employed in these systems, traditional prefetchers provide significant benefits.