ARM Community: Software Enablement - ARM Community

Introduction
In the information era with its increased use of mobile devices to communicate and access information, web browsers constitute the central component to navigate through the vast amount of information as they are able to fetch and visualize content spread across the world-wide data network known as the Internet. Over the last decade, visualization capabilities of web browsers have been greatly enhanced by the increase in processing power of general purpose CPUs and graphics accelerators. Most mobile platforms include general-purpose SIMD engine, such as ARM NEON which can be used to efficiently process multimedia formats and help enhance user experience – up to a 4x improvement as discussed in this article.

Background
The web browser group at the ...

The new DS-5 Community Edition brings CPU and GPU statistics together to speed up Android games and applications

Game Developers Conference (GDC), San Francisco - These are very special days for Android application developers targeting ARM processor-based devices.

On March 2nd the version of the ARM® Development Studio 5 (DS-5™) toolchain dedicated to Android native application developers, the DS-5 Community Edition (CE), was selected as finalist for the Eclipse Community Awards in the ...

Video is increasingly becoming an important and essential part of consumer electronics. Video centric features like augmented reality and video conferencing provide enhanced visual user interaction. Such features are now expected across a wide variety of application segments. In the embedded world, intensive video compression is typically done using standard DSP’s or specialized hardware accelerators, as they can provide both the specialized functionality and the high level of performance required. However, now ARM processors with NEON™ technology can be as capable of compressing video as some dedicated hardware, and do so with greater power efficiency.

H.264/MPEG-4 AVC (Advanced Video Coding) is currently one of the most commonly used formats for the recording, compression, and distribution of video content. The H.264 video format has a very broad application range that covers all forms of digital compressed video from low bit-rate Internet streaming applications to HDTV broadcast. With the use of H.264, bit rate savings of 50% or more ar...

Finding one's way through references to ARM processors is not always obvious.
This article is the first of a series on ARM fundamentals that will introduce various topics to help you get more familiar with the ARM architecture. It aims at helping you to better understand ARM processors, starting with explaining how they are named, and then showing how knowing your processor matters by introducing a few of their recent features.

If you are curious about what is in your pretty electronic device or are a developer willing to understand how to start getting the best out of your processor, you may find some useful information here. The second part of the article may be technically a bit more challenging than the first, but don't worry! The few code samples are only concrete examples used to illustrate the explanations. The specific details are not necessary to understand the global picture.

The first step is to understand how ARM processors are referenced: it certainly sounds nice, but what is this "dual Cortex-A9, based on ARMv7" in your super-phone?

Processor fami...

ARM Development Studio 5 (DS-5) is the software development tool that sets the standard for ARM with its optimising compiler, its extensible and easy to use debugger, and its unique analysis tool, Streamline. But DS-5 is not just for the ARM IP: if you're the designer of an ARM based SoC, an operating system that supports ARM or have productivity tools that support ARM, you can join the DS-5 ecosystem to make sure that your customers also get the DS-5 experience. Here are 10 ways you can do it.

1. Add DS-5 debug support to your ARM based SoC. The DS-5 debugger has a target database that is extensible by you,...

The ARM architecture has been used for many years in mobile phones and electronic devices, but it is only relatively recently that the architecture has diversified into being used in laptops, tablets and smartphones. There are now many companies that have adopted the ARM architecture as the basis for their next world-beating technology product. This is great, but the problem is that if you are new to the ARM architecture and want to start writing programs for an ARM processor, where do you start? What document do you need to read first before you dive into the library of technical information that is available on the ARM InfoCenter?

My choice would be the recently released Cortex A-Series Programmer's Guide. This guide provides a gentle in...

The 2010 ARM Technology Conference (Techcon) is taking place in Santa Clara next week. A large number of companies will be presenting their solutions to support development and optimization of products based on ARM technology, and open source will be discussed in many of these with projects like Linux, Android and development tools. For instance, many of these solutions are using open source to leverage earlier work that ARM has done with the open source community, contributing CPU and architecture support to the upstream Linux kernel and GNU compilation tools ahead of partner silicon platforms being available. One of the most recent illustrations is the contribution of Cortex-A15 CPU support to the Linux kernel as the processor was announced. Linux kernel and GNU development tools are key building blocks to support the development of solutions such as Android, ...

It was always about the code (and where it would be used!)

When I was a software developer I would often find that the project team I was in would try to guess how many devices the code would eventually run on. So at the launch of the Cortex-A15 last week one of the main points that hit home for me was just how wide the spectrum of power and performance points the Cortex-A family of processors could cover - from feature phone to superphone, tablet to DTV, home server to web server etc. This means that a developer could now find their software running across a huge range of devices in the future.

So is it the same software?

Absolutely. Cortex-A15 is based on the same ARMv7A architecture that the other Cortex-A processors use, therefore allowing the exact same application code to run on all of them, from a ...

We have seen how to load and store data with NEON, and how to handle the leftovers resulting from vector processing. Let us move on to doing some useful data processing – multiplying matrices.

Matrices

In this post, we will look at how to efficiently multiply four-by-four matrices together, an operation frequently used in the world of 3D graphics. We will assume that the matrices are stored in memory in column-major order – this is the format used by OpenGL-ES.

Algorithm

We start by examining the matrix mutiply operation in detail, by expanding the calculation, and identifying sub-operations that can be implemented using NEON instructions.

Notice that in the diagram, we multiply each column of the first matrix (in red) by a corresponding single value in the second matrix (blue) then add together the results for each element to give a column of results. This operation is repeated for each of the four columns in the result matrix.

...

In the first post on NEON about loads and stores we looked at transferring data between the NEON processing unit and memory. In this post, we deal with an often encountered problem: input data that is not a multiple of the length of the vectors you want to process. You need to handle the leftover elements at the start or end of the array - what is the best way to do this on NEON?

Leftovers

Using NEON typically involves operating on vectors of data from four to sixteen elements in length. Frequently, you will find that your array is not a multiple of that length, and you have to process those leftover elements separately.

For example, you want to load, process and store eight elements per iteration using NEON, but your array is 21 elements long. The first two iterations go well, but for the third, there are only five elements remaining to be processed. What do you do?

Fixing Up

There are three ways to handle these leftovers. The methods vary in requirements, performance, and code size. They are listed below in order, with the fastest approach first.

Larger Arrays

If you can change the size of the arrays that you are processing, increase the length of the array to the next multiple of the vector size using padding elements. This allows you to read and write beyond the end of your data without corrupting ad...