QNX's Fabulous Concept Cars


Thomas Bloor
Business Development Manager, BlackBerry

If you’ve been to CES chances are you’ve seen one of our concept cars, even if you’ve not been to our booth, we take these to our industry partners. Now as we start gearing up for next year’s CES there are some great innovations in the pipeline. (I’ve seen them, but I’m not telling.) So as I can’t spill the beans on what's coming, but let’s take a look at some of my favorite QNX Concept Cars from years past.


The Porsche 911 Carrera (CES 2012)
Admittedly I have a soft spot for performance cars, but the Porsche deserves headline billing in the roster as a CNet "Best of CES" winner. With revolutionary (for 2012), cloud-based voice recognition you could control the navigation system using natural language.   And, text-to-speech meant that you could listen to incoming BBMs, emails and text messages. Rounding out the roster of features that would still be considered ahead of the curve for a production car today, this model featured one-touch Bluetooth pairing.  Simply touching your phone to an NFC reader in the center console automatically paired the phone and car. 



The Bentley Continental GT (CES 2013)
In an outburst of Canadian quirkiness, we decided that when better to do a photoshoot of a Bentley Convertible than in the middle of the Canadian winter? Of course despite the -20C (-4F) weather we’d have to have the top down!

The cold and the snow do not detract from the revolutionary center stack with DLP® display from Texas Instruments. This immense (for 2013) featured an organically curved surface and TI’s optical touch input technology, which allowed physical control knobs to be mounted directly on the screen resulting in an ideal balance in physical and touchscreen controls



Taking natural language voice recognition a step further we worked with AT&T’s WatsonSM . Say "Hello Bentley," and the car's voice recognition system immediately starts interacting with you, in a distinctly British accent, old chap.


If that weren’t enough, the cluster displays the back-up camera and user configurable high resolution instrumentation. We also took the mobile office to new heights with smartphone integration with streaming music, email notification, news feeds, and other real-time information. Put the Bentley into park and you could fire up video conferencing with realistic telepresence.  

Separate cameras for the driver and passenger provide independent video streams, while high-definition voice technology from QNX offers expanded bandwidth for greater realism, while stereo telepresence makes the remote caller sound as if they’re sitting right next to you.


Mercedes CLA 45 AMG (CES 2014)
Have you looked inside a Mercedes S class recently? The horizontally orientated center stack display extends across the dash. Coincidentally our 2014 Mercedes concept had a 21-inch-wide center display extending towards the passenger enabling a seamless interaction with the vehicle.
 
Behind the scenes the Cluster was integrated with the center stack running both driver information and IVI functions. With seamless controllability across the touch screen, physical buttons and the jog wheel controls multi-modal input was highlighted across all available functionality. 

Not content with that, we foreshadowed greater integration of ADAS functionality warnings to the driver through both the cluster and verbally through text to speech if the local speed limits were exceeded.

Jeep Wrangler and Toyota Highlander
Now it’s not all high end luxury cars, which is just as well because they never let me drive any of them. Our Jeep Wrangler and Toyota Highlanders serve as our QNX reference vehicles showcasing what the QNX CAR application platform can do, straight out of the box. Additionally, the Toyota features our advances in in-car communication and acoustics platforms enabling an enhanced user experience for drivers and passengers.

These cars are not just  "show floor wonders" because our automotive knowledge enables us to build demonstrators for the real world, which can be driven, and the technology can be experienced first-hand. Concept clusters and displays abound, but real vehicle bus integration means these cars are drivable with real instrumentation and connectivity.


While I can’t reveal what new exciting technologies we are planning for CES 2017 (believe me, you’ll want to come and take a look), I can say that our reference vehicles are currently on tour so keep an eye open for them on the roads near you.




Firing up the Ignition Interpreter

V8 and other modern JavaScript engines get their speed via just-in-time (JIT) compilation of script to native machine code immediately prior to execution. Code is initially compiled by a baseline compiler, which can generate non-optimized machine code quickly. The compiled code is analyzed during runtime and optionally re-compiled dynamically with a more advanced optimizing compiler for peak performance. In V8, this script execution pipeline has a variety of special cases and conditions which require complex machinery to switch between the baseline compiler and two optimizing compilers, Crankshaft and TurboFan.

One of the issues with this approach (in addition to architectural complexity) is that the JITed machine code can consume a significant amount of memory, even if the code is only executed once. In order to mitigate this overhead, the V8 team has built a new JavaScript interpreter, called Ignition, which can replace V8’s baseline compiler, executing code with less memory overhead and paving the way for a simpler script execution pipeline.

With Ignition, V8 compiles JavaScript functions to a concise bytecode, which is between 50% to 25% the size of the equivalent baseline machine code. This bytecode is then executed by a high-performance interpreter which yields execution speeds on real-world websites close to those of code generated by V8’s existing baseline compiler.

In Chrome 53, Ignition will be enabled for Android devices which have limited RAM (512 MB or less), where memory savings are most needed. Results from early experiments in the field show that Ignition reduces the memory of each Chrome tab by around 5%.

V8’s compilation pipeline with Ignition enabled.

Details


In building Ignition’s bytecode interpreter, the team considered a number of potential implementation approaches. A traditional interpreter, written in C++ would not be able to interact efficiently with the rest of V8’s generated code. An alternative would have been to hand-code the interpreter in assembly code, however given V8 supports nine architecture ports, this would have entailed substantial engineering overhead.

Instead, we opted for an approach which leveraged the strength of TurboFan, our new optimizing compiler, which is already tuned for optimal interaction with the V8 runtime and other generated code. The Ignition interpreter uses TurboFan’s low-level, architecture-independent macro-assembly instructions to generate bytecode handlers for each opcode. TurboFan compiles these instructions to the target architecture, performing low-level instruction selection and machine register allocation in the process. This results in highly optimized interpreter code which can execute the bytecode instructions and interact with the rest of the V8 virtual machine in a low-overhead manner, with a minimal amount of new machinery added to the codebase.

Ignition is a register machine, with each bytecode specifying its inputs and outputs as explicit register operands, as opposed to a stack machine where each bytecode would consume inputs and push outputs on an implicit stack. A special accumulator register is an implicit input and output register for many bytecodes. This reduces the size of bytecodes by avoiding the need to specify specific register operands. Since many JavaScript expressions involve chains of operations which are evaluated from left to right, the temporary results of these operations can often remain in the accumulator throughout the expression’s evaluation, minimizing the need for operations which load and store to explicit registers.

As the bytecode is generated, it passes through a series of inline-optimization stages. These stages perform simple analysis on the bytecode stream, replacing common patterns with faster sequences, remove some redundant operations, and minimize the number of unnecessary register loads and transfers. Together, the optimizations further reduce the size of the bytecode and improve performance.

For further details on the implementation of Ignition, see our BlinkOn talk:


Future


Our focus for Ignition up until now has been to reduce V8’s memory overhead. However, adding Ignition to our script execution pipeline opens up a number of future possibilities. The Ignition pipeline has been designed to enable us to make smarter decisions about when to execute and optimize code to speed up loading web pages and reduce jank and to make the interchange between V8’s various components more efficient.

Stay tuned for future developments in Ignition and V8.

by Ross McIlroy, V8 Ignition Jump Starter
12:01:00 PM

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