ARM ,processor of new era

ARM processor

The ARM processor is a 32-bit RISC processor, meaning it is built using the reduced instruction set computer (RISC) instruction set architecture (ISA). ARM processors are microprocessors and are widely used in many of the mobile phones sold each year, as many as 98% of mobile phones. They are also used in personal digital assistants (PDA), digital media and music layers, hand-held gaming systems,calculators, and even computer hard drives.

The first ARM processor-based computer was the Acorn Archimedes, released in 1987. Apple Computer became involved with helping to improve the ARM technology in the late 1980s, with their work resulting in the ARM6 technology in 1992. Later, Acorn used the ARM6-based ARM 610 processor in their Risc PC computers in 1994. Today, the ARM architecture is licensed for use by many companies, including Apple, Cirrus Logic, Intel, LG, Microsoft, NEC, Nintendo, Nvidia, Sony, Samsung, Sharp, Texas Instruments, Yamaha, and many more. The latest developed ARM processor families include ARM11 and Cortex. ARM processors capable of 64-bit processing are currently in development.

ARM Processor Architecture

ARM architecture forms the basis for every ARM processor. Over time, the ARM architecture has evolved to include architectural features to meet the growing demand for new functionality, high performance and the needs of new and emerging markets. There are currently two ARMv8 profiles, the ARMv8-A architecture profile for high performance markets such as mobile and enterpise, and the ARMv8-R architecture profile for embedded applications in automotive and industrial control.

The ARM architecture supports implementations across a wide range of performance points, establishing it as the leading architecture in many market segments. The ARM architecture supports a very broad range of performance points leading to very small implementations of ARM processors, and very efficient implementations of advanced designs using state of the art micro-architecture techniques. Implementation size, performance, and low power consumption are key attributes of the ARM architecture.

ARM developed architecture extensions to provide support for Java acceleration (Jazelle®), security (TrustZone®), SIMD, and Advanced SIMD (NEON™) technologies. The ARMv8-architecture adds a Cryptographic extension as an optional feature.

The ARM architecture is similar to a Reduced Instruction Set Computer (RISC) architecture, as it incorporates these typical RISC architecture features:

A uniform register file load/store architecture, where data processing operates only on register contents, not directly on memory contents.

Simple addressing modes, with all load/store addresses determined from register contents and instruction fields only.

Enhancements to a basic RISC architecture enable ARM processors to achieve a good balance of high performance, small code size, low power consumption and small silicon area.

References:

http://www.arm.com/

What is cloud?

Computing as a service over the Internet

Cloud computing is the delivery of on-demand computing resources—everything from applications to data centres—over the Internet on a pay-for-use basis.

Types Of Cloud Computing Services:

• Software As A Service
• Platform As A Service
• Infrastructure As A Service

Software As A Service(SaaS):

Cloud-based applications—or software as a service (SaaS)—run on distant computers “in the cloud” that are owned and operated by others and that connect to users’ computers via the Internet and, usually, a web browser.

Platform As A Service(PaaS):

Platform as a service provides a cloud-based environment with everything required to support the complete life cycle of building and delivering web-based (cloud) applications—without the cost and complexity of buying and managing the underlying hardware, software, provisioning and hosting.

Infrastructure As A Service(IaaS):

Infrastructure as a service provides companies with computing resources including servers, networking, storage, and data centre space on a pay-per-use basis.

Types Of Cloud:

• Public Cloud
• Private Cloud
• Hybrid Cloud

Public Cloud:

Public clouds are owned and operated by companies that use them to offer rapid access to affordable computing resources to other organisations or individuals. With public cloud services, users don’t need to purchase hardware, software or supporting infrastructure, which is owned and managed by providers.

Private Cloud:

A private cloud is owned and operated by a single company that controls the way virtualised resources and automated services are customised and used by various lines of business and constituent groups. Private clouds exist to take advantage of many of cloud’s efficiencies, while providing more control of resources and steering clear of multi-tenancy.

Hybrid Cloud:

A hybrid cloud uses a private cloud foundation combined with the strategic use of public cloud services. The reality is a private cloud can’t exist in isolation from the rest of a company’s IT resources and the public cloud. Most companies with private clouds will evolve to manage workloads across data centres, private clouds and public clouds—thereby creating hybrid clouds.

References:

www.ibm.com

                                                             What is a GPU??

            “A graphics processing unit (GPU) is a specialized electronic circuit designed to rapidly manipulate and alter memory to accelerate the building of images in a frame buffer intended for output to a display.”

Origins of GPUs

• As said before, GPUs were created to perform a specific task: real-time 3D rendering

– Before GPUs: the CPU had to perform all this

– Fun fact: MMX extensions (soon to be called SSE) appeared more or less at the same time

• Other extensions created over time include:

– IEEE-754 floating-point co-processors (early 1980s)

– Physics Processing Units (PPUs)

– Etc.General Processing

General Processing Using GPUs

• Started in early 2000s

– Diverted shader/vertex/etc. units within a GPU (e.g. instead of storing color information, use the 32-bit word to store an integer or floating-point value)

• While doable, programming was basically hell

– Needed to divert OpenGL commands to do your 

computation

– Not all computations can easily be mapped to triangles and/or polygons…

• Everything changed around 2006, with NVIDIA introducing GPUs which started to get more generic, including a C-based programming language (CUDA).

Features of Current GPUs

• Boards have their own memory. 

– Usually between 1 and 2 GB 

• can go up to 6 GB on high-end models

– Much faster than the processor’s memory.

– Higher bandwidth than the processor’s memory.

• Massive Parallelism

– GPUS support thousands of threads running at the same time.

Example of NVIDIA GPU

• NVIDIA GPU has 32,768 registers

– Divided into lanes

– Each SIMD thread is limited to 64 registers

– SIMD thread has up to:

• 64 vector registers of 32 32-bit elements

• 32 vector registers of 32 64-bit elements

– Fermi has 16 physical SIMD lanes, each containing 2048 registers.

References :

http://www.nvidia.com/content/PDF/fermi_white_papers/NVIDIA_Fermi_Compute_Architecture_Whitepaper.pdf.

https://drive.google.com/file/d/0B3lhf6u9E9inajctME5ncmE5TDg/edit?usp=sharing 4G TechnologY..

Hello Friends, I'm Chaitanya More,Studying in third year computer engineering at Pune Institute Of Computer Technology ,Pune.. Im glad to write my first post to blog. stay connected for more technological things..