The document discusses the architecture and implementation of the ARM Cortex-A8 microprocessor. It introduces the Cortex-A8 as ARM's first applications microprocessor that delivers high performance and power efficiency for mobile and consumer applications. Key features include the Thumb-2 instruction set, NEON media processing, TrustZone security, and an integrated L2 cache. The Cortex-A8 achieves further performance gains through a dual-issue pipeline and deeper pipeline than prior ARM processors. It employs a combination of synthesized, structured, and custom implementation techniques to optimize for aggressive power, performance and area targets.
The document provides an overview of the ARM Cortex-A8 processor, including its RISC-based superscalar design, 13-stage instruction pipeline, branch prediction features, and NEON SIMD capabilities. The Cortex-A8 achieves high performance while maintaining low power usage. It is widely used in mobile devices and consumer electronics due to its versatility and balance of performance and energy efficiency.
Hand gesture recognition system(FYP REPORT)Afnan Rehman
This document is a final year project report submitted by three students - Afnan Ur Rehman, Haseeb Anser Iqbal, and Anwaar Ul Haq - for their bachelor's degree in computer science. The report describes the development of a hand gesture recognition system using computer vision and machine learning techniques. Key aspects of the project include image acquisition using a webcam, preprocessing the images using techniques like filtering and noise removal, detecting and cropping the hand region, extracting HU moments features, training a classifier on sample gesture images, and classifying new images using KNN. The system is also able to translate recognized gestures to speech using text-to-speech.
This document presents a real-time hand gesture recognition method. It discusses algorithms like 3D model-based, skeletal-based, and appearance-based for hand gesture recognition. The process involves hand detection, tracking, segmentation, and recognition. Features, advantages, and applications are also covered. The method uses fast hand tracking, segmentation, and multi-scale feature extraction for accurate recognition. It concludes with discussing potential for continued progress in areas like sign language recognition and accessibility.
The document provides an overview of the ARM Cortex-A8 processor, including its RISC-based superscalar design, 13-stage instruction pipeline, branch prediction features, and NEON SIMD capabilities. The Cortex-A8 achieves high performance while maintaining low power usage. It is widely used in mobile devices and consumer electronics due to its versatility and balance of performance and energy efficiency.
Hand gesture recognition system(FYP REPORT)Afnan Rehman
This document is a final year project report submitted by three students - Afnan Ur Rehman, Haseeb Anser Iqbal, and Anwaar Ul Haq - for their bachelor's degree in computer science. The report describes the development of a hand gesture recognition system using computer vision and machine learning techniques. Key aspects of the project include image acquisition using a webcam, preprocessing the images using techniques like filtering and noise removal, detecting and cropping the hand region, extracting HU moments features, training a classifier on sample gesture images, and classifying new images using KNN. The system is also able to translate recognized gestures to speech using text-to-speech.
This document presents a real-time hand gesture recognition method. It discusses algorithms like 3D model-based, skeletal-based, and appearance-based for hand gesture recognition. The process involves hand detection, tracking, segmentation, and recognition. Features, advantages, and applications are also covered. The method uses fast hand tracking, segmentation, and multi-scale feature extraction for accurate recognition. It concludes with discussing potential for continued progress in areas like sign language recognition and accessibility.
The document discusses and compares several Intel processor architectures and product lines, including:
- Core 2 Duo, an older dual-core architecture that is being replaced by newer Intel processors.
- Core i3, i5, and i7, which use the newer Nehalem/Sandy Bridge/Ivy Bridge architectures. The Core i3 is the budget option with dual-cores while i5 and i7 have quad-cores.
- Differences between the architectures include instruction handling, number of threads, and features like Turbo Boost. The newer architectures generally provide better performance, even at similar clock speeds to older designs.
Deep Learning techniques have enabled exciting novel applications. Recent advances hold lot of promise for speech based applications that include synthesis and recognition. This slideset is a brief overview that presents a few architectures that are the state of the art in contemporary speech research. These slides are brief because most concepts/details were covered using the blackboard in a classroom setting. These slides are meant to supplement the lecture.
This document discusses ARM Cortex-M microcontrollers and their features. It provides information on ARM architecture and RISC processors. Specific Cortex-M models are described including their instruction sets, pipelines, registers and memory architecture. STM32 microcontrollers are mentioned. General purpose input/output and how to configure pins for different functions like GPIO, analog or alternate functions are explained. Examples of working with registers to read button states and toggle LEDs are provided. The concept of bit banding memory is also introduced.
This document describes the implementation of a Sobel edge detection algorithm on an FPGA. It discusses first and second order derivative edge detection algorithms. It provides an overview of the FPGA implementation including the use of block RAM for image storage, a VGA interface for display, and resource utilization. The FPGA implementation achieved a processing speed of 400 frames per second for a 500x500 grayscale image. Future work proposed improving performance and developing the design into a complete embedded system on a Zynq SoC.
Chroma from Luma Intra Prediction for AV1Luc Trudeau
Chroma from Luma Intra Prediction for AV1
This presentation summarizes chroma from luma intra prediction, a new tool in the AV1 video codec. It predicts chroma pixel values from reconstructed luma pixels within the same block. The technique combines subsampling and averaging, then applies a scaling factor to the luma-derived values. Scaling factors range from -2 to 2 and are jointly signaled using an entropy coded probability table. Test results show average bitrate savings of 0.4-1.0% for various content, with gains over 4% for some gaming scenes. Future work may expand the technique to inter prediction and explore non-linear prediction models.
The document discusses graphics processing units (GPUs). It provides three key points:
1. A GPU is a specialized microprocessor that accelerates the rendering of 2D and 3D graphics. It allows for faster drawing of polygons, textures, and images to improve rendering speed.
2. GPUs were originally developed in the 1990s by Nvidia and helped popularize 3D graphics. Modern GPUs contain hundreds of processing cores and have memory bandwidths up to 230GB/s.
3. GPUs are used across many devices from embedded systems and mobile phones to PCs and game consoles. They accelerate graphics tasks through parallel processing compared to conventional CPUs.
1) The document discusses shortest path algorithms and their application to traffic assignment problems, comparing the performance of CPU vs GPU implementations.
2) It finds that GPU implementations can be 45x faster than CPU for problems with massive parallelizable data like traffic simulations.
3) However, GPU programming requires more specialized knowledge and hardware restrictions limit accessibility, while CPU remains more flexible but less optimized for large datasets.
CXL is an open standard for connecting CPUs, GPUs, and accelerators that maintains memory coherency. It aims to provide high-speed, low-latency connections while enabling these devices to directly access each other's memory. CXL builds on PCIe physically but introduces new protocols for memory coherency and acceleration that make it well-suited for AI, machine learning, and high performance computing workloads. CXL devices come in three types - Type 1 devices have caches, Type 2 devices have local memory accessible by the CPU, and Type 3 devices are memory expanders.
CPUs have multiple cores and are suited for a variety of tasks requiring low latency, while GPUs have many smaller cores optimized for parallel processing. GPUs can perform thousands of basic operations simultaneously. Though CPUs and GPUs both process data, CPUs are designed for serial tasks and general computing while GPUs are specialized for graphics processing and parallel tasks like those in AI and supercomputing. Efficient parallel processing is what allows GPUs to outperform CPUs for certain applications.
Performance Comparison Between x86 and ARM AssemblyManasa K
This document compares performance between x86 and ARM processors. It discusses that x86 uses CISC architecture and is more complex, while ARM uses RISC architecture and has simpler instructions. For a task of multiplying two numbers in memory, x86 uses a single complex instruction while ARM uses multiple simpler load, multiply and store instructions. While x86 has shorter code, ARM keeps operands in registers reducing need to reload from memory. Overall, ARM has advantages of lower power consumption and efficiency making it suitable for portable devices, while x86 focuses on performance for desktops and servers.
Optical character recognition (ocr) pptDeijee Kalita
The document discusses optical character recognition (OCR), which is the process of converting scanned images of printed or handwritten text into machine-encoded text. It provides a brief history of OCR, explaining some of the early developments. It also outlines the typical steps involved, including pre-processing, character recognition, and post-processing. Examples of applications of OCR technology are given.
The document discusses the ARM Cortex A15 processor. It was designed by ARM and began production in late 2011 for market in late 2012. Key features include NEON for SIMD operations, a VFPv4 floating point unit, Thumb-2 instruction encoding, and TrustZone security. Applications include smartphones, computing devices, and digital home entertainment systems.
www.ISEFundHub.com is a new investor portal that provides information on investment funds listed on the Irish Stock Exchange (ISE) to professional investors. The portal includes information from a wide range of investment funds across different domiciles. It allows investors to easily compare and screen funds using analytics tools, and fund managers can customize profiles for their funds and publish news and documents.
The document discusses and compares several Intel processor architectures and product lines, including:
- Core 2 Duo, an older dual-core architecture that is being replaced by newer Intel processors.
- Core i3, i5, and i7, which use the newer Nehalem/Sandy Bridge/Ivy Bridge architectures. The Core i3 is the budget option with dual-cores while i5 and i7 have quad-cores.
- Differences between the architectures include instruction handling, number of threads, and features like Turbo Boost. The newer architectures generally provide better performance, even at similar clock speeds to older designs.
Deep Learning techniques have enabled exciting novel applications. Recent advances hold lot of promise for speech based applications that include synthesis and recognition. This slideset is a brief overview that presents a few architectures that are the state of the art in contemporary speech research. These slides are brief because most concepts/details were covered using the blackboard in a classroom setting. These slides are meant to supplement the lecture.
This document discusses ARM Cortex-M microcontrollers and their features. It provides information on ARM architecture and RISC processors. Specific Cortex-M models are described including their instruction sets, pipelines, registers and memory architecture. STM32 microcontrollers are mentioned. General purpose input/output and how to configure pins for different functions like GPIO, analog or alternate functions are explained. Examples of working with registers to read button states and toggle LEDs are provided. The concept of bit banding memory is also introduced.
This document describes the implementation of a Sobel edge detection algorithm on an FPGA. It discusses first and second order derivative edge detection algorithms. It provides an overview of the FPGA implementation including the use of block RAM for image storage, a VGA interface for display, and resource utilization. The FPGA implementation achieved a processing speed of 400 frames per second for a 500x500 grayscale image. Future work proposed improving performance and developing the design into a complete embedded system on a Zynq SoC.
Chroma from Luma Intra Prediction for AV1Luc Trudeau
Chroma from Luma Intra Prediction for AV1
This presentation summarizes chroma from luma intra prediction, a new tool in the AV1 video codec. It predicts chroma pixel values from reconstructed luma pixels within the same block. The technique combines subsampling and averaging, then applies a scaling factor to the luma-derived values. Scaling factors range from -2 to 2 and are jointly signaled using an entropy coded probability table. Test results show average bitrate savings of 0.4-1.0% for various content, with gains over 4% for some gaming scenes. Future work may expand the technique to inter prediction and explore non-linear prediction models.
The document discusses graphics processing units (GPUs). It provides three key points:
1. A GPU is a specialized microprocessor that accelerates the rendering of 2D and 3D graphics. It allows for faster drawing of polygons, textures, and images to improve rendering speed.
2. GPUs were originally developed in the 1990s by Nvidia and helped popularize 3D graphics. Modern GPUs contain hundreds of processing cores and have memory bandwidths up to 230GB/s.
3. GPUs are used across many devices from embedded systems and mobile phones to PCs and game consoles. They accelerate graphics tasks through parallel processing compared to conventional CPUs.
1) The document discusses shortest path algorithms and their application to traffic assignment problems, comparing the performance of CPU vs GPU implementations.
2) It finds that GPU implementations can be 45x faster than CPU for problems with massive parallelizable data like traffic simulations.
3) However, GPU programming requires more specialized knowledge and hardware restrictions limit accessibility, while CPU remains more flexible but less optimized for large datasets.
CXL is an open standard for connecting CPUs, GPUs, and accelerators that maintains memory coherency. It aims to provide high-speed, low-latency connections while enabling these devices to directly access each other's memory. CXL builds on PCIe physically but introduces new protocols for memory coherency and acceleration that make it well-suited for AI, machine learning, and high performance computing workloads. CXL devices come in three types - Type 1 devices have caches, Type 2 devices have local memory accessible by the CPU, and Type 3 devices are memory expanders.
CPUs have multiple cores and are suited for a variety of tasks requiring low latency, while GPUs have many smaller cores optimized for parallel processing. GPUs can perform thousands of basic operations simultaneously. Though CPUs and GPUs both process data, CPUs are designed for serial tasks and general computing while GPUs are specialized for graphics processing and parallel tasks like those in AI and supercomputing. Efficient parallel processing is what allows GPUs to outperform CPUs for certain applications.
Performance Comparison Between x86 and ARM AssemblyManasa K
This document compares performance between x86 and ARM processors. It discusses that x86 uses CISC architecture and is more complex, while ARM uses RISC architecture and has simpler instructions. For a task of multiplying two numbers in memory, x86 uses a single complex instruction while ARM uses multiple simpler load, multiply and store instructions. While x86 has shorter code, ARM keeps operands in registers reducing need to reload from memory. Overall, ARM has advantages of lower power consumption and efficiency making it suitable for portable devices, while x86 focuses on performance for desktops and servers.
Optical character recognition (ocr) pptDeijee Kalita
The document discusses optical character recognition (OCR), which is the process of converting scanned images of printed or handwritten text into machine-encoded text. It provides a brief history of OCR, explaining some of the early developments. It also outlines the typical steps involved, including pre-processing, character recognition, and post-processing. Examples of applications of OCR technology are given.
The document discusses the ARM Cortex A15 processor. It was designed by ARM and began production in late 2011 for market in late 2012. Key features include NEON for SIMD operations, a VFPv4 floating point unit, Thumb-2 instruction encoding, and TrustZone security. Applications include smartphones, computing devices, and digital home entertainment systems.
www.ISEFundHub.com is a new investor portal that provides information on investment funds listed on the Irish Stock Exchange (ISE) to professional investors. The portal includes information from a wide range of investment funds across different domiciles. It allows investors to easily compare and screen funds using analytics tools, and fund managers can customize profiles for their funds and publish news and documents.
The document discusses the student's horror trailer project. It analyzes how their trailer fits the horror genre conventions and is influenced by specific horror films and trailers. The student explains how they used pacing, music, editing, and other techniques to build suspense and shock value. They aimed to recreate styles from trailers such as Evil Dead, The Conjuring, and The Woman in Black. Alfred Hitchcock served as the key auteur influence in terms of using effective montage sequences to heighten tension and scare factors.
The document presents statistics from various sources about content marketing strategies and their effectiveness. It finds that companies with documented content marketing strategies consider themselves more effective than those without, and that creating engaging content and measuring campaigns are top priorities for many organizations. It also shares findings about the use and effectiveness of different social media platforms for content marketing.
Unalligned versus natureally alligned memory accessAneesh Raveendran
This document discusses aligned versus unaligned memory access. It notes that unaligned access occurs when accessing N bytes of data from an address not evenly divisible by N. While some architectures can handle unaligned access, it reduces performance or causes exceptions. The compiler ensures structures and variables are aligned, but unaligned access can occur from casts or pointer arithmetic. The get_unaligned() and put_unaligned() macros or memcpy() can be used to avoid unaligned access issues.
Evaluation Question 1: In what ways does your media product use, develop or c...LydiaGreenwood
The document discusses the student's horror trailer project. It analyzes how their trailer fits the horror genre conventions by including gore, jump scares, and psychological elements. It also examines how their trailer replicates specific techniques from films like Don't Be Afraid of the Dark and The Hunger Games, such as jump scares, creature designs, and a sympathetic main character. The student discusses using pacing, music, editing, and intertitles to build suspense. They analyzed horror trailers like Evil Dead and The Conjuring to replicate dramatic reveal techniques. Alfred Hitchcock's use of montage influenced the student's own editing style. Overall, the document provides a thorough self-evaluation of the student's horror trailer and
Transforming learning with new technologiestonikaperry
Traditional teaching styles do not engage today's students. Modern learners require active and technology-integrated lessons. The document then reviews several digital tools like Future Me, ViewPure, QR Voice, Prezi, and Padlet that can be used to engage students and incorporate technology into lessons. These tools allow students to set goals, view videos without ads, create multimedia presentations, and participate in interactive discussions. Integrating such technologies better attracts students' attention and increases their achievement.
Resources Valley provides free educational resources for students and researchers online. They offer materials to help with assignments, thesis writing, dissertation development, and research methods. Example topics covered include Chicago citation styles, essay writing, data analysis, teaching practices, and research proposals. The resources are intended to benefit students from school through graduate level, as well as academic researchers. Users can search categories and download resources to access and share the materials.
SFO15-406: ARM FDPIC toolset, kernel & libraries for Cortex-M & Cortex-R mmul...Linaro
SFO15-406: ARM FDPIC toolset, kernel & libraries for Cortex-M & Cortex-R mmuless cores
Speakers:
Date: September 24, 2015
★ Session Description ★
ARM FDPIC toolset and kernel patches makes it possible to boot a mmu-less Linux kernel and support userland applications which rely on dynamic loading. No source change are needed to compiler the application (compared to the BFLAT model). The presentation will focus on the toolset structure and characteristics and give some insights on the FDPIC ABI.
★ Resources ★
Video: https://www.youtube.com/watch?v=TNRNQNEcwVI
Presentation: http://www.slideshare.net/linaroorg/sfo15406-arm-fdpic-toolset-kernel-libraries-for-cortexm-cortexr-mmuless-cores
Etherpad: pad.linaro.org/p/sfo15-406
Pathable: https://sfo15.pathable.com/meetings/303078
★ Event Details ★
Linaro Connect San Francisco 2015 - #SFO15
September 21-25, 2015
Hyatt Regency Hotel
http://www.linaro.org
http://connect.linaro.org
A brief idea on ARM Cortex-R series. Its comparison with Arm A and Arm M series processors.Applications of Arm Cortex R series in Texas Instruments microcontroller.
The document discusses the features and architecture of the ARM9 processor. It describes the ARM9 as having a 5-stage pipeline, 32 registers, and support for both ARM and Thumb instruction sets. It supports DSP enhancements like single-cycle 32x16 multiplication and saturating arithmetic. The ARM9 powers applications in devices like smartphones, networking equipment, automotive systems, and embedded devices. The document then focuses on the specific ARM920T processor, which adds a 16KB cache and memory management unit to the ARM9 core.
The ARM architecture describes a family of RISC-based processors designed and licensed by ARM Holdings. It uses a RISC approach requiring fewer transistors than traditional processors. This allows for lower costs, less heat and power usage, making ARM processors suitable for portable battery-powered devices like smartphones and tablets. Companies can build low-energy system-on-a-chip devices incorporating memory, interfaces, radios, etc using ARM's simpler design.
Arm Cortex A8 Vs Intel Atom:Architectural And Benchmark Comparisonsnapoleaninlondon
This document compares the ARM Cortex-A8 and Intel Atom processor architectures through a review of their specifications and benchmark performance tests. Specifically, it analyzes the architectural details of the Cortex-A8 and Atom N330, and benchmarks a Texas Instruments OMAP3530-based Cortex-A8 system (BeagleBoard) against an Intel Atom N330 desktop PC. The benchmarks show the Atom has higher raw performance, while the Cortex-A8 has significantly greater power efficiency. Overall, the document provides a concise overview and performance comparison of the two architectures for mobile and low-power applications.
The ARM architecture is a popular RISC architecture used in low-power embedded systems like mobile phones and consumer electronics due to its low cost and power efficiency. It utilizes features like conditional execution, load/store architecture, and 16 32-bit registers to achieve good performance despite its simpler design compared to processors like x86. The ARM instruction set was later augmented with the more dense Thumb instruction set to improve code size. ARM processors are widely used in consumer devices and supported by many embedded operating systems.
The document discusses instruction sets and processor architectures. It provides details about the ARM and SHARC processors. ARM is a reduced instruction set computer (RISC) used in consumer electronic devices due to its small size, low power consumption, and reduced complexity. It allows multiprocessing and has tightly coupled memory. SHARC is a digital signal processor (DSP) chip with on-chip memory, parallel processing capabilities, and support for integer and floating point operations. It uses a very long instruction word (VLIW) and has addressing modes for accessing external memory. The document also covers basic input/output programming and characteristics of I/O devices that interface with processors through registers.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Smartphones architecture is generally different from
common desktop architectures. It is limited by power, size and
cost of manufacturing with the goal to provide the best
experience for users in a minimum cost. Stemming from this
fact, modern micro-processors are designed with an
architecture that has three main components: an application
processor that executes the end user’s applications, a modem
responding to baseband radio activities, and peripheral devices
for interacting with the end user.
Parallelism
Multicores:
The Cortex A7 MPCore processor implements the ARMv7-A
architecture. The Cortex A7 MPCore processor has one to
four processors in a single multi-processor device. The
following figure shows an example configuration with four
processors [3].
In this paper, we are discussing the architecture of the
application processor of Apple iPhone. Specifically, Apple
iPhone uses ARM Cortex generation of processors as their
core. The following sections discusses this architecture in terms
of Instruction Set Architecture, Memory Hierarchy and
Parallelism.
The document discusses ARM microprocessors and embedded systems. It provides an overview of ARM including that it was established in 1990 as a joint venture and licenses RISC microprocessor designs. It describes the wide use of ARM processors in devices like mobile phones and discusses key aspects of ARM processors like their low power consumption and high code density making them suitable for embedded applications. It also summarizes the RISC design philosophy implemented in ARM and describes the typical components of an ARM-based embedded system including the processor, peripherals, controllers and bus.
How to Select Hardware for Internet of Things Systems?Hannes Tschofenig
With the increasing commercial interest in Internet of Things (IoT) the question about a reasonable hardware configuration surfaces again and again.
Peter Aldworth, a hardware engineer with more than 19 years of experience, discusses this topic in a presentation given to the IETF community.
This document presents a design for a Near Field Communication (NFC) tag architecture that provides security using the AES encryption algorithm controlled by an 8-bit microcontroller. The architecture includes a framing logic unit, 8-bit microcontroller, cryptographic unit, and memory unit. The microcontroller controls data transmission and reception between these units. The cryptographic unit implements the AES algorithm using a controller, RAM, and data path. Implementation in VHDL showed the design requires significantly less area than previous state machine-based approaches. Future work will analyze attacks and further reduce the area requirement.
ARM 32-bit Microcontroller Cortex-M3 introductionanand hd
What is the ARM Cortex-M3 processor?
Architecture Versions,Processor naming, Instruction Set Development, The Thumb-2 Technology and Instruction Set Architecture, Cortex-M3 Processor Applications
Design of a low power processor for Embedded system applicationsROHIT89352
The document describes the design of a low power processor for embedded systems. It uses clock gating techniques and a standby mode to reduce power consumption. The processor is designed based on a modified MIPS microarchitecture and can operate using the RV32E instruction set. It has been implemented at the register transfer level in Verilog and synthesized into an 180nm CMOS technology. The processor consumes 189uA in normal mode and 11.1uA in standby mode, achieving low power operation.
- Thumb is a 16-bit instruction set extension to the 32-bit ARM architecture that provides higher code density and smaller memory requirements compared to standard ARM code.
- Thumb instructions are 16-bits wide while ARM instructions are 32-bits wide, allowing Thumb code to be half the size of equivalent ARM code.
- Thumb code executes on ARM processors by decompressing Thumb instructions into their 32-bit ARM equivalents on the processor.
Balance, Flexibility, and Partnership: An ARM Approach to Future HPC Node Arc...Eric Van Hensbergen
The document discusses ARM's approach to future high performance computing (HPC) node architectures. It advocates for balance, flexibility, and partnership in developing exascale systems. ARM believes that a heterogeneous approach using different core types optimized for various workloads, flexible memory technologies, and partnerships to develop the software ecosystem will help overcome challenges in achieving exascale performance while improving power efficiency.
An embedded system is a specialized computer system that is part of a larger mechanical or electrical system. It performs predefined tasks, unlike a general purpose computer. The document discusses embedded systems and provides examples like refrigerators and mobile phones. It also describes microprocessors, microcontrollers, and the 8051 microcontroller architecture in detail. Applications of embedded systems mentioned include signal processing, distributed control, and small systems.
Welcome to International Journal of Engineering Research and Development (IJERD)IJERD Editor
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arm 7 microprocessor architecture ans pin diagram.pptmanikandan970975
ARM Ltd is a company that designs ARM processor cores. It was founded in 1990 as a spin-off from Acorn Computers. ARM licenses its core designs to other companies who manufacture and sell chips containing ARM cores. While ARM does not manufacture chips itself, it develops technologies like software tools and debug hardware to assist partners using ARM architectures. Current low-end ARM cores include the ARM7TDMI, which features a Thumb instruction set, debug support, an enhanced multiplier, and embedded debug hardware. The ARM7TDMI uses a von Neumann architecture and has a 3-stage pipeline.
The LPC2148 microcontroller features a 32-bit ARM7TDMI-S CPU, 32-512KB of onboard flash memory, and 8-40KB of static RAM. It operates at speeds up to 60MHz and includes interfaces such as USB 2.0, UARTs, I2C, SPI, and timers. Its small size and low power consumption make it well-suited for applications requiring miniaturization like access control and point-of-sale devices.
A 32-Bit Parameterized Leon-3 Processor with Custom Peripheral IntegrationTalal Khaliq
A new descriptive method to use ARM AHB and APB Bus architecture to add new IP Cores and enhance functionality of 32 bit Processor (Leon3). AHB and APB addressing and GUI enhancement is also discussed.
Similar to Architecture and Implementation of the ARM Cortex-A8 Microprocessor (20)
The document discusses single electron transistors (SETs). SETs use controlled electron tunneling through nanoscale islands to precisely control electric current. This allows SETs to function as extremely sensitive switches and amplifiers at the scale of single electrons. The document outlines how SETs work, describing their tunnel junction structure and coulomb blockade effect. It also discusses their potential applications in quantum computing and sensing and challenges to overcome before they can be implemented in complex circuits.
Universal Asynchronous Receive and transmit IP coreAneesh Raveendran
This document describes a Universal Asynchronous Receive and Transmit (UART) IP core. It discusses the RS-232 serial communication protocol that the UART uses. It then provides details on the design specification of the UART IP core, including its 9-pin connector, data formats, and configurable baud rates. The document also describes the internal design of the UART transmitter and receiver blocks, including how they convert parallel data to serial and vice versa.
Branch prediction is necessary to reduce penalties from branches in modern deep pipelines. It predicts the direction (taken or not taken) and target of branches. Common techniques include bimodal prediction using saturating counters and two-level prediction using branch history tables and pattern history tables. Real processors use hybrid predictors combining different techniques. Mispredictions require flushing the pipeline and incur a performance penalty.
This document discusses instruction pipelining in computer processors. It begins by defining pipelining and explaining how it works like an assembly line to increase throughput. It then discusses different types of pipelines and introduces the MIPS instruction pipeline as an example. The document goes on to explain different types of pipeline hazards like structural hazards, control hazards, and data hazards. It provides examples of how to detect and resolve these hazards through techniques like forwarding, stalling, predicting, and delayed branching. Key concepts covered include pipeline registers, control signals, forwarding units, and branch prediction buffers.
Reversible logic gates can be used to reduce heat generation in computing. Traditional irreversible logic gates necessarily generate heat from information loss, but reversible gates avoid this by not resulting in information loss. The document describes several types of reversible gates: the NOT gate, Feynman gate, Toffoli gate, and Fredkin gate. It provides details on the functionality of each gate through logic equations and VHDL code examples.
Design and Implementation of Bluetooth MAC core with RFCOMM on FPGAAneesh Raveendran
The System-on-Chip (SoC) design of digital circuits makes the technology to be reusable. The current paper describes an aspect of design and implementation of IEEE 802.15.1 (Bluetooth) protocol on Field Programmable Gate Array (FPGA) based SoC. The Bluetooth is a wireless technology designed as a short-range connectivity solution for personal, portable and handheld electronic devices.
This design aims on Bluetooth technology with serial
communication (RS-232) profile at the application layer.
The IP core consists of Bluetooth Medium Access Control
(MAC) and Universal Asynchronous Receiver/Transmitter
(UART). Each module of the design is described and
developed with hardware description language-Very High
Speed Integrated Circuit Hardware Description Language
(VHDL). The final version of SoC is implemented and
tested with ALTERA STRATIX II EP2S15672C3 FPGA.
Design of FPGA based 8-bit RISC Controller IP core using VHDLAneesh Raveendran
This paper describes the design, development and
implementation of an 8-bit RISC controller IP core. The
controller has been designed using Very high speed integrated circuit Hardware Description Language (VHDL). The design constraints are speed, power and area. This controller is efficient for specific applications and suitable for small applications. This non-pipelined controller has four units: - Fetch, Decode, Execute and a stage control unit. It has an in built program and data memory. Also it has four ports for communicating with other I/O devices. A hierarchical approach has been used so that basic units can be modeled using behavioral programming. The basic
units are combined using structural programming. The design
has been implemented using ALTERA STRATIX II FPGA
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
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CI/CD with in UiPath
End-to-end overview of CI/CD pipeline with Azure devops
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UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
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Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
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1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
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What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
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Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
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My slides at Nordic Testing Days 6.6.2024
Climate impact / sustainability of software testing discussed on the talk. ICT and testing must carry their part of global responsibility to help with the climat warming. We can minimize the carbon footprint but we can also have a carbon handprint, a positive impact on the climate. Quality characteristics can be added with sustainability, and then measured continuously. Test environments can be used less, and in smaller scale and on demand. Test techniques can be used in optimizing or minimizing number of tests. Test automation can be used to speed up testing.
Climate Impact of Software Testing at Nordic Testing Days
Architecture and Implementation of the ARM Cortex-A8 Microprocessor
1. Architecture and Implementation of the ARM Cortex-A8 Microprocessor
ANEESH R
aneeshr2020@gmail.com
Architecture and Implementation of the ARM Cortex-A8 Microprocessor
1 Introduction
The ARM® Cortex™-A8 microprocessor is the first applications microprocessor in ARM’s new Cortex
family. With high performance and power efficiency, it targets a wide variety of mobile and consumer
applications including mobile phones, set-top boxes, gaming consoles and automotive
navigation/entertainment systems. The Cortex-A8 processor spans a range of performance points
depending on the implementation, delivering over to 2000 Dhrystone MIPS (DMIPS) of performance for
demanding consumer applications and consuming less than 300mW for low-power mobile devices. This
translates into a large increase in processing capability while staying with the power levels of previous
generations of mobile devices. Consumer applications will benefit from the reduced heat dissipation
and resulting lower packaging and integration costs.
It is the first ARM processor to incorporate all of the new technologies available in the ARMv7
architecture. New technologies seen for the first time include NEON™ for media and signal processing
and Jazelle® RCT for acceleration of real-time compilers. Other technologies recently introduced that
are now standard on the ARMv7 architecture include TrustZone® technology for security, Thumb®-2
technology for code density and the VFPv3 floating point architecture.
2 Overview of the Cortex Architecture
The unifying technology of Cortex processors is Thumb-2 technology. The Thumb-2 instruction set
combines 16- and 32-bit instructions to improve code density and performance. The original ARM
instruction set consists of fixed-length 32-bit instructions, while the Thumb instruction set employs 16bit instructions. Because not all operations mapped into the original Thumb instruction set, multiple
instructions were sometimes needed to emulate the task of one 32-bit instruction.
Thumb-2 technology adds about 130 additional instructions to Thumb. The added functionality removes
the need to switch between ARM and Thumb modes in order to service interrupts, and gives access to
the full set of processor registers. The resulting code maintains the traditional code density of Thumb
instructions while running at the performance levels of 32-bit ARM code. Entire applications can now be
written in Thumb-2 technology, removing the original architecture required for mode switching.
An entire application can be written using space-saving Thumb-2 instructions, whereas with the original
Thumb mode the processor had to switch between ARM and Thumb modes.
Making its first appearance in an ARM processor is the NEON media and signal processing technology
targeted at audio, video and 3D graphics. It is a 64/128-bit hybrid SIMD architecture. NEON technology
has its own register file and execution pipeline which are separate from the main ARM integer
pipeline. It can handle both integer and single precision floating-point values, and includes support for
unaligned data accesses and easy loading of interleaved data stored in structure form. Using NEON
technology to perform typical multimedia functions, the Cortex-A8 processor can decode MPEG-4 VGA
video (including dering, deblock filters and yuv2rgb) at 30 frames/sec at 275 MHz, and H.264 Video at
350 MHz
aneeshr2020@gmail.com
Aneesh R
2. Architecture and Implementation of the ARM Cortex-A8 Microprocessor
ANEESH R
aneeshr2020@gmail.com
Also new is Jazelle RCT technology, an architecture extension that cuts the memory footprint of just-intime (JIT) bytecode applications to a third of their original size. The smaller code size results in a boost
performance and a reduction of power.
TrustZone technology is included in the Cortex-A8 to ensure data privacy and DRM protection in
consumer products like mobile phones, personal digital assistants and set-top boxes that run open
operating systems. Implemented within the processor core, TrustZone technology protects peripherals
and memory against a security attack. A secure monitor within the core serves as a gatekeeper
switching the system between secure and non-secure states. In the secure state, the processor runs
“trusted” code from a secure code block to handle security-sensitive tasks such as authentication and
signature manipulation.
Besides contributing to the processor's signal processing performance, NEON technology enables
software solutions to data processing applications. The result is a flexible platform which can
accommodate new algorithms and new applications as they emerge with simply the download of new
software or a driver.
The VFPv3 technology is an enhancement to the VFPv2 technology. New features include a doubling of
the number of double-precision registers to 32, and the introduction of instructions that perform
conversions between fixed-point and floating-point numbers.
3 Exploring Features of the Cortex-A8 Microarchitecture
The Cortex-A8 processor is the most sophisticated low-power design yet produced by ARM. To achieve
its high levels of performance, new microarchitecture features were added which are not traditionally
found in the ARM architecture, including a dual in-order issue ARM integer pipeline, an integrated L2
cache and a deep 13-stage pipe.
Fig: ARM Cortex-A8 architecture
aneeshr2020@gmail.com
Aneesh R
3. Architecture and Implementation of the ARM Cortex-A8 Microprocessor
ANEESH R
aneeshr2020@gmail.com
3.1 Super scalar pipeline
Perhaps the most significant of these new features is the dual-issue, in-order, statically scheduled ARM
integer pipeline. Previous ARM processors have only a single integer execution pipeline. The ability to
issue two data processing instructions at the same time significantly increases the maximum potential
instructions executed per cycle. It was decided to stay with in-order issue to keep additional power
required to a minimum. Out-of-order issue and retire can require extensive amounts of logic consuming
extra power. The choice to go with in-order also allows for fire-and-forget instruction issue, thus
removing critical paths from the design and reducing the need for custom design in the pipeline. Static
scheduling allows for extensive clock gating for reduced power during execution.
The dual ALU (arithmetic logic unit) pipelines (ALU 0 and ALU 1) are symmetric and both can handle
most arithmetic instructions. ALU pipe 0 always carries the older of a pair of issued instructions. The
Cortex-A8 processor also has multiplier and load-store pipelines, but these do not carry additional
instructions to the two ALU pipelines. These can be thought of as “dependent” pipelines. Their use
requires simultaneous use of one of the ALU pipelines. The multiplier pipeline can only be coupled with
instructions that are in ALU 0 pipelines, whereas the load-store pipeline can be coupled with instructions
in either ALU.
3.2 Branch prediction
The 13-stage pipeline was selected to enable significantly higher operating frequencies than previous
generations of ARM microarchitectures. Note that stage F0 is not counted because it is only address
generation. To minimize the branch penalties typically associated with a deeper pipeline, the Cortex-A8
processor implements a two-level global history branch predictor. It consists of two different structures:
the Branch Target Buffer (BTB) and the Global History Buffer (GHB) which are accessed in parallel with
instruction fetches.
The BTB indicates whether or not the current fetch address will return a branch instruction and its
branch target address. It contains 512 entries. On a hit in the BTB a branch is predicted and the GHB is
accessed. The GHB consists of 4096 2-bit saturating counters that encode the strength and direction
information of branches. The GHB is indexed by 10-bit history of the direction of the last ten branches
encountered and 4 bits of the PC.
In addition to the dynamic branch predictor, a return stack is used to predict subroutine return
addresses. The return stack has eight 32-bit entries that store the link register value in r14 (register 14)
and the ARM or Thumb state of the calling function. When a return-type instruction is predicted taken,
the return stack provides the last pushed address and state.
3.3 Level-1 cache
The Cortex-A8 processor has a single-cycle load-use penalty for fast access to the Level-1 caches. The
data and instruction caches are configurable to 16k or 32k. Each is 4-way set associative and uses a
Hash Virtual Address Buffer (HVAB) way prediction scheme to improve timing and reduce power
consumption. The caches are physically addressed (virtual index, physical tag) and have hardware
support for avoiding aliased entries. Parity is supported with one parity bit per byte.
aneeshr2020@gmail.com
Aneesh R
4. Architecture and Implementation of the ARM Cortex-A8 Microprocessor
ANEESH R
aneeshr2020@gmail.com
The replacement policy for the data cache is write-back with no write allocates. Also included is a store
buffer for data merging before writing to main memory.
The HVAB is a novel approach to reducing the power required for accessing the caches. It uses a
prediction scheme to determine which way of the RAM to enable before an access.
3.4
Level-2 cache
The Cortex-A8 processor includes an integrated Level-2 cache. This gives the Level-2 cache a dedicated
low latency, high bandwidth interface to the Level-l cache. This minimizes the latency of Level-1 cache
linefills and does not conflict with traffic on the main system bus. It can be configured in sizes from 64k
to 2M.
The Level-2 cache is physically addressed and 8-way set associative. It is a unified data and instruction
cache, and supports optional ECC and Parity. Write back, write through, and write-allocate policies are
followed according to page table settings. A pseudo-random allocation policy is used. The contents of
the Level-1 data cache are exclusive with the Level-2 cache, whereas the contents of the Level-1
instruction cache are a subset of the Level-2 cache. The tag and data RAMs of the Level-2 cache are
accessed serially for power savings.
3.5 Neon-media engine
The Cortex-A8 processor’s NEON media processing engine pipeline starts at the end of the main integer
pipeline. As a result, all exceptions and branch mispredictions are resolved before instructions reach
it. More importantly, there is a zero load-use penalty for data in the Level-1 cache. The ARM integer
unit generates the addresses for NEON loads and stores as they pass through the pipeline, thus allowing
data to be fetched from the Level-1 cache before it is required by a NEON data processing
operation. Deep instruction and load-data buffering between the NEON engine, the ARM integer unit
and the memory system allow the latency of Level-2 accesses to be hidden for streamed data. A store
buffer prevents NEON stores from blocking the pipeline and detects address collisions with the ARM
integer unit accesses and NEON loads.
aneeshr2020@gmail.com
Aneesh R
5. Architecture and Implementation of the ARM Cortex-A8 Microprocessor
ANEESH R
aneeshr2020@gmail.com
The NEON unit is decoupled from the main ARM integer pipeline by the NEON instruction queue
(NIQ). The ARM Instruction Execute Unit can issue up to two valid instructions to the NEON unit each
clock cycle. NEON has 128-bit wide load and store paths to the Level-1 and Level-2 cache, and supports
streaming from both.
The NEON media engine has its own 10 stage pipeline that begins at the end ARM integer
pipeline. Since all mispredicts and exceptions have been resolved in the ARM integer unit, once an
instruction has been issued to the NEON media engine it must be completed as it cannot generate
exceptions. NEON has three SIMD integer pipelines, a load-store/permute pipeline, two SIMD singleprecision floating-point pipelines, and a non-pipelined Vector Floating-Point unit (VFPLite).
NEON instructions are issued and retired in-order. A data processing instruction is either a NEON
integer instruction or a NEON floating-point instruction. The Cortex-A8 NEON unit does not parallel
issue two data-processing instructions to avoid the area overhead with duplicating the data-processing
functional blocks, and to avoid timing critical paths and complexity overhead associated with the muxing
of the read and write register ports.
The NEON integer datapath consists of three pipelines: an integer multiply/accumulate pipeline (MAC),
an integer Shift pipeline, and an integer ALU pipeline. A load-store/permute pipeline is responsible for
all NEON load/stores, data transfers to/from the integer unit, and data permute operations such as
interleave and de-interleave. The NEON floating-point (NFP) datapath has two main pipelines: a
multiply pipeline and an add pipeline. The separate VFPLite unit is a non-pipelined implementation of
the ARM
VFPv3 Floating Point Specification targeted for medium performance IEEE 754 compliant floating point
support. VFPLite is used to provide backwards compatibility with existing ARM floating point code and
to provide IEEE 754 compliant single and double precision arithmetic. The “Lite” refers to area and
performance, not functionality.
aneeshr2020@gmail.com
Aneesh R
6. Architecture and Implementation of the ARM Cortex-A8 Microprocessor
ANEESH R
aneeshr2020@gmail.com
4 Implementation
Because of the aggressive performance, power, and area targets (PPA) of the Cortex-A8 processor, new
implementation flows have been developed in order to meet goals without resorting to a full-custom
implementation. The resulting flows enable fine tuning of the design to the desired application. The
result is fundamentally a cell-based flow, but under it lies semi-custom techniques that have been used
where necessary to meet performance.
The Cortex-A8 processor uses a combination of synthesized, structured, and custom circuits. The design
was divided into seven functional units and then subdivided into blocks, and the appropriate
implementation technique chosen for each. Since the entire design is synthesizeable, blocks that can
easily meet their PPA goals can stick with a standard synthesis flow.
A structured flow is used for blocks which contain logic that can take advantage of controlled placement
and routing approach to meet timing or area goals. This approach is a semi-custom flow that manually
maps the block into a gate-level netlist and specifies a relative placement for all the cells in the
block. The relative placement does not specify the exact locations of the cells but how each cell is
placed with respect to the other cells in the block.
The structured approach is typically used for data blocks that have regular structure. The logic
implementation and technology mapping of the block is done manually to maintain the regular dataoriented bus structure of the block instead of generating a random gate structure through
synthesis. The logic gates of the block are placed according to the flow of data through the block. This
approach offers more control over the design than an automated synthesis approach and leads to a
more predictable timing closure. It is also possible to get better performance and area on complex,
high-performance designs than traditional techniques. The resulting netlists may be interpreted with
traditional tiling techniques using the ARM Artisan® Advantage-CE™ or compatible library.
The Artisan Advantage-CE library contains more than a thousand cells. Besides the standard cells used
typical synthesis libraries, many tactical cells are included more in line with custom implementation
techniques. These are used in an automated fashion in the structured flow. The library is specifically
designed to deal with the high-density routing requirements of high-performance processors with a
focus on both high speed operation and low static and dynamic power. Leakage reduction is achieved
through power gating MT-CMOS cells and retention flip-fops to support sleep and standby modes. ARM
has worked with tool vendors to ensure support for this critical new flow.
Finally, a few of the most critical timing and area sensitive blocks of the design are reserved for full
custom techniques. This includes memory arrays, register files and scoreboards. These blocks contain a
mix of static and dynamic logic. No self-timed circuits are used.
5 Conclusion
The Cortex-A8 processor is the fastest, most power-efficient microprocessor yet developed by
ARM. With the ability to decode VGA H.264 video in under 350MHz, it provides the media processing
power required for next generation wireless and consumer products while consuming less than 300mW
in 65nm technologies. Its new NEON technology provides a platform for flexible software-based
solutions for media processing. Thumb-2 instructions provide code density while maintaining the
performance of standard ARM code; Jazelle RCT technology does likewise for realtime
compilers. TrustZone technology provides security for sensitive data and DRM.
Many significant new microarchitecture features make their first appearance on the Cortex-A8
processor. These include a dual issue, in-order superscalar pipeline, an integrated Level-2 cache and a
aneeshr2020@gmail.com
Aneesh R
7. Architecture and Implementation of the ARM Cortex-A8 Microprocessor
ANEESH R
aneeshr2020@gmail.com
significantly deeper pipeline than precious ARM processors. To meet its aggressive performance targets
while maintaining ARM’s traditional small power budget, new flows have been developed which
approach the efficiency of custom techniques while keeping the flexibility of an automated flow. The
Cortex-A8 processor is a quantum jump in flexible low power, high-performance processing.
aneeshr2020@gmail.com
Aneesh R