computer science

Tegra

Tegra is a computer science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Tegra rather than just read about it. In short: Tegra is a system on a chip (SoC) series developed by Nvidia for mobile devices such as smartphones, personal digital assistants, and mobile Internet devices. The Tegra integrates an ARM architecture central processing unit (CPU), graphics processing unit (GPU), northbridge, southbridge, and memory controller onto one package.

Key takeaways

Tegra belongs to computer science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Tegra to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Tegra from memory before moving on to harder problems.

Reference excerpt

Tegra is a system on a chip (SoC) series developed by Nvidia for mobile devices such as smartphones, personal digital assistants, and mobile Internet devices. The Tegra integrates an ARM architecture central processing unit (CPU), graphics processing unit (GPU), northbridge, southbridge, and memory controller onto one package. Early Tegra SoCs are designed as efficient multimedia processors. The Tegra-line evolved to emphasize performance for gaming and machine learning applications without sacrificing power efficiency, before taking a drastic shift in direction towards platforms that provide vehicular automation with the applied Nvidia Drive brand name on reference boards and its semiconductors; and with the Nvidia Jetson brand name for boards adequate for AI applications (e.g. within robots or drones) and for various smart high-level automation purposes.

History The Tegra APX 2500 was announced on February 12, 2008. The Tegra 6xx product line was revealed on June 2, 2008, and the APX 2600 was announced in February 2009. The APX chips were designed for smartphones, while the Tegra 600 and 650 chips were intended for smartbooks and mobile Internet devices (MID). The first product to use the Tegra was Microsoft's Zune HD media player in September 2009, followed by the Samsung M1. Microsoft's Kin was the first cellular phone to use the Tegra; however, the phone did not have an app store, so the Tegra's power did not provide much advantage. In September 2008, Nvidia and Opera Software announced that they would produce a version of the Opera 9.5 browser optimized for the Tegra on Windows Mobile and Windows CE. At Mobile World Congress 2009, Nvidia introduced its port of Google's Android to the Tegra. On January 7, 2010, Nvidia officially announced and demonstrated its next generation Tegra system-on-a-chip, the Nvidia Tegra 250, at Consumer Electronics Show 2010. Nvidia primarily supports Android on Tegra 2, but booting other ARM-supporting operating systems is possible on devices where the bootloader is accessible. Tegra 2 support for the Ubuntu Linux distribution was also announced on the Nvidia developer forum. Nvidia announced the first quad-core SoC at the February 2011 Mobile World Congress event in Barcelona. Though the chip was codenamed Kal-El, it is now branded as Tegra 3. Early benchmark results show impressive gains over Tegra 2, and the chip was used in many of the tablets released in the second half of 2011. In January 2012, Nvidia announced that Audi had selected the Tegra 3 processor for its In-Vehicle Infotainment systems and digital instruments display. The processor will be integrated into Audi's entire line of vehicles worldwide, beginning in 2013. The process is ISO 26262-certified. In summer of 2012 Tesla Motors began shipping the Model S electric sedan, which contains two NVIDIA Tegra 3D Visual Computing Modules (VCM). One VCM powers the 17-inch touchscreen infotainment system, and one drives the 12.3-inch all digital instrument cluster." In March 2015, Nvidia announced the Tegra X1, the first SoC to have a graphics performance of 1 teraflop. At the announcement event, Nvidia showed off Epic Games' Unreal Engine 4 "Elemental" demo, running on a Tegra X1. On October 20, 2016, Nvidia announced that the Nintendo Switch hybrid video game console will be powered by Tegra hardware. On March 15, 2017, TechInsights revealed the Nintendo Switch is powered by a custom Tegra X1 (model T210), with lower clockspeeds.

Models

Tegra APX Tegra APX 2500 Processor: ARM11 600 MHz MPCore (originally GeForce ULV) Suffix: APX (formerly CSX) Memory: NOR or NAND flash, Mobile DDR Graphics: Image processor (FWVGA 854×480 pixels) Up to 12 megapixels camera support LCD controller supports resolutions up to 1280×1024 Storage: IDE for SSD Video codecs: up to 720p MPEG-4 AVC/H.264 and VC-1 decoding Includes GeForce ULV support for OpenGL ES 2.0, Direct3D Mobile, and programmable shaders Output: HDMI, VGA, composite video, S-Video, stereo jack, USB USB On-The-Go Tegra APX 2600 Enhanced NAND flash Video codecs: 720p H.264 Baseline Profile encode or decode 720p VC-1/WMV9 Advanced Profile decode D-1 MPEG-4 Simple Profile encode or decode

Tegra 6xx Tegra 600 Targeted for GPS segment and automotive Processor: ARM11 700 MHz MPCore Memory: low-power DDR (DDR-333, 166 MHz) SXGA, HDMI, USB, stereo jack HD camera 720p Tegra 650 Targeted for GTX of handheld and notebook Processor: ARM11 800 MHz MPCore Low power DDR (DDR-400, 200 MHz) Less than 1 watt envelope HD image processing for advanced digital still camera and HD camcorder functions Display supports 1080p at 24 frame/s, HDMI v1.3, WSXGA+ LCD and CRT, and NTSC/PAL TV output Direct support for Wi-Fi, disk drives, keyboard, mouse, and other peripherals A complete board support package (BSP) to enable fast time to market for Windows Mobile-based designs

Tegra 2

The second generation Tegra SoC has a dual-core ARM Cortex-A9 CPU, an ultra low power (ULP) GeForce GPU, a 32-bit memory controller with either LPDDR2-600 or DDR2-667 memory, a 32 KB/32 KB L1 cache per core and a shared 1 MB L2 cache. Tegra 2's Cortex A9 implementation does not include ARM's SIMD extension, NEON. There is a version of the Tegra 2 SoC supporting 3D displays; this SoC uses a higher clocked CPU and GPU. The Tegra 2 video decoder is largely unchanged from the original Tegra and has limited support for HD formats. The lack of support for high-profile H.264 is particularly troublesome when using online video streaming services. Common features:

CPU cache: L1: 32 KB instruction + 32 KB data, L2: 1 MB 40 nm semiconductor technology

1 Pixel shaders : Vertex shaders : Texture mapping units : Render output units

Devices

Tegra 3

… excerpt ends here. Continue reading the full article.

Illustrations

Worked examples

Example 1 — a first encounter with Tegra

Start with the simplest possible case. Write down what Tegra claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In computer science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Tegra before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Tegra ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Tegra

In research: Tegra appears in computer science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Tegra in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Tegra is common in secondary-school and first-year university syllabi. It links to neighbouring topics ARM-based systems on chips, Mobile computing, Nvidia hardware, so understanding it makes those chapters shorter.
In everyday life: Look for Tegra outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Tegra in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Tegra means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Tegra out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Tegra in simple terms?

Why does Tegra matter?

Because it connects several computer science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Tegra?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Tegra.