Modern vehicles require high-end GPUs especially when they are employed for autonomous driving. Here’s all you should be aware of about the state of the GPUs in cars.
Over the past decade, the auto industry has experienced tremendous growth. One of the biggest milestones for the industry was the advent of inexpensive efficient, reliable, and powerful electric vehicles.
In addition, we discovered a new technological breakthrough: autonomous driving.
It is true that the AI driver is very far from being perfect however when enough effort is put into research and processing technology, cars will eventually be able to autonomously drive.
However, in order to power the artificial intelligence that is present in Tesla, BMW, Porsche, or any other car that requires an efficient graphics processor (and the CPU) is required. In reality, GPUs are an integral component of all new vehicles in the present.
This article will highlight the importance of graphics cards in the vehicle or autonomous vehicle driving.
Tesla’s infotainment systems in Model S Plaid. Model S Plaid
Before we go into the complexities regarding artificial intelligence and autonomous vehicle and the roles that the GPU should play in the future, let’s talk about some of the most basic reasons that automobiles require graphics cards.
It’s not a secret that all modern vehicles that are in use today feature a display. Like other displays, a computer is required (GPU) for rendering the picture.
The graphics cards used in the majority of automobiles aren’t as efficient as AMD’s or NVIDIA’s most powerful GPUs.
However, this doesn’t mean they’re not capable however, the tasks they’re required to complete are much simpler. For instance, rendering or processing the interface of the car with whom the user interacts.
Certain cars have weaker CPUs/GPUs, leading to an inefficient (not quick) touchscreen. A weaker GPU can also limit the use of other features.
Here are a few features used in cars of today that require a powerful GPU:
New car models are often equipped with an array of features in the infotainment system, which can help the driver.
These days, parking cameras are important, particularly for vehicles with a lot of dead angles similar to the majority of SUVs. There are a variety of options for installing cameras in the back, front, or sides that can assist the driver in avoiding bumps into other vehicles or scraping sidewalks.
Naturally, in order to handle all these sensors and cameras it is necessary for the vehicle to have a GPU in order to process the picture. But rendering images from a camera isn’t extremely demanding, therefore, you can assume that GPUs aren’t that efficient either.
Bird’s Eye View and Environment
360-degree/bird’s eye view in a Mercedes-Benz X-Class
To improve the functionality the quality of this feature, businesses are using more sophisticated sensors and cameras that can detect things in the area. The most recent invention is the bird’s-eye view parking assist.
This is definitely a more intricate feature than just having a couple of cameras that record the car’s dead angles. This is because the GPU is now required to handle the sensor data and live to render all the surrounding environment surrounding the vehicle to ensure that drivers get a better perception of the surrounding.
To make these capabilities possible automobile manufacturers have to utilize the most powerful GPUs. When we have realistic renders There could be car graphics that are better than the most powerful graphics cards available today such as AMD’s RX 6900XT and NVIDIA’s RTX 3090.
A different, but not so new option can be found in the head-up display or HUD. The primary purpose behind HUD is to stop the driver from gazing down at the instruments and display all the necessary information on the windshield.
This can be accomplished by the projection of images onto windshields. Another option is a dedicated transparent display placed on top of the windscreen. This is where the data is projected. A car HUD is typically utilized as a speedometer, as well as a GPS aid.
In the photo in the image below, the instrument cluster inside the BMW serves as a speedometer and also displays GPS directions. This eliminates the need to look off the roadway.
A heads-up display is displayed on the windshield of the BMW E60
This isn’t an extremely demanding task for the car’s GPU However, it is required to deal with other things too and therefore requires a powerful GPU.
The Growth Of Autonomous Driving
Nuro is a true self-driving delivery vehicle
The concept of autonomous vehicles (also known as Advanced Driver Aided Systems (ADAS) can be said to mean that vehicles in the near coming years will no longer be controlled by humans unless it is absolutely necessary. In the end, this eliminates human error from the equation, which will make vehicular transportation more efficient, faster and much more secure.
It will take time to achieve the level of autonomy required to develop the perfect AI driver.
It’s a good thing, Advanced Driver Assisted Systems have seen a significant increase in the number of people who were using them following the release of Tesla’s electric vehicles (like Model X, Model S, and Model 3) Model S, Model X Model 3 and Model 3) came out with an autopilot that it’s never been seen before.
After that, other manufacturers within the automotive industry began offering their own electric cars equipped with similar driver-assist features.
The role of GPUs in Autonomous Driving
We’ve already delved into autonomous driving, and how GPUs are required to process information while when driving. However, let’s dive deeper and talk about how GPUs as well as technology giants such as NVIDIA, AMD, and Intel are now part of the automobile industry.
The daily and highway traffic is extremely complicated, which implies that cars require strong hardware to manage all of those “autopilot” computations.
Every car is equipped with a CPU, sometimes referred to as an ECU (the heart of the whole operation) however, it isn’t capable of processing the data to allow autonomous driving.
This is where the graphics cards are able to help. As opposed to processors GPU is able to dedicate its massive processing power to specific kinds of tasks. For instance, in automobiles the GPU process a variety of visual information from sensors, cameras and so on. Then, it is utilized to automate driving.
NVIDIA’s Self-Driving Technology
NVIDIA is a major component of the auto sector that deals with self-driving technology. It is most likely the top company in this area.
At present, NVIDIA is partnered with Audi, Jaguar Land Rover, Mercedes-Benz, NIO, Volkswagen and Volvo Cars. We believe that this group of companies will expand.
Although Tesla does not utilize NVIDIA hardware to power its autopilot or infotainment systems, nor does it use NVIDIA hardware system, they have an NVIDIA-powered computer with five thousand A100 graphics. The supercomputer handles Tesla’s AI training, which helps to develop their autopilot system.
NVIDIA A100 GPU
Hyperion from DRIVE
Businesses like Audi or Mercedes-Benz have stayed with NVIDIA due to their Hyperion DRIVE system for self-driving vehicles.
The computer’s architecture is completely focused on autonomous driving. It’s specifically designed to process data from sensors and cameras to give the most enjoyable auto-driving experience.
NVIDIA claims it’s DRIVE Hyperion has also been found to be extremely customizable, which is what brands are searching for.
To reap the advantages that come with using the DRIVE Hyperion platform the vehicle must be fitted with a DRIVE orin SOC.
The term”system-on-a-chip” (or SoC) signifies that all essential components required for a computer are built into the chip. Technically, DRIVE Orin is not just a GPU. it is a part of the chip and plays an important role to play in the self-driving system.
With the capabilities provided by Orin SOC, and the power of Orin SOC, Level 5 autonomous driving is now possible. The Level 5 technology implies that there is no need for drivers to be present. Previous versions of ORIN such as that of DRIVE AGX Pegasus and Xavier could only offer Level 2 and Level 3 self-driving.
DRIVE Atlan SOC Vizualised
We all know that NVIDIA continuously strives for improvement and technological advancements, such as their Orin chips or Tensor cores that make up their GPUs to manage DLSS.
Therefore, naturally, Orin’s successor is being developed. Atlan is the latest version of NVIDIA’s Drive. Atlan will offer 11,000 TOPS of computer power.
AMD’s Role In Cars
AMD isn’t used widely in the automotive sector, but AMD has teamed up in partnership with Tesla in order to run their vehicle’s infotainment system.
At present, Tesla has the most efficient infotainment system in the world.
Do you want to know the most important thing?
When the Model S Plaid was revealed, Tesla Model S Plaid, Elon Musk stated that the infotainment system is PS5-level performance because of AMD’s Ryzen processor which can provide 10-TFLOPS computing capacity.
Elon Musk proved these claims by showing a Cyberpunk 2077-themed game through the Model S’ infotainment system. That’s quite remarkable.
The APU inside it has the RDNA2 GPU which allows the Tesla to play games that are demanding like the CP2077.
Here’s a short video of the Cyberpunk 2077 action within the Model S Plaid.
What is the reason Tesla Customers Need a High-Performance GPU?
While Tesla’s incredibly powerful infotainment technology has been praised, it could make some people wonder what the point is of it.
Here’s the thing:
Tesla is close the point of fully automatic driving. So in the near term, when the car is able to take all the driving users can be able to enjoy every kind of entertainment available through the car’s display. From watching movies on Netflix to gaming at the highest level.
Cuphead + Tesla announcement
Even now, having an efficient GPU can be beneficial since when Tesla users are at the charge station they are able to simply play a few games to make waiting times only a bit more enjoyable.
Intel In The Automotive Industry
Prior to when Tesla made the switch on AMD’s Ryzen APU, they relied on Intel Atom. Its Atom chip was considerably slower, but was powerful enough to manage Tesla’s infotainment system.
Intel has also partnered together with Audi before to create the level 3 automated driving technology.
Intel is also advertising its Intel FPGAs that can speed up the manufacturing of Advanced Driver Assisted Systems.
Intel’s FPGAs focus on safety, flexibility security, efficiency and flexibility However, as of now we aren’t sure whether they’re being utilized in any automobile.
We do know that Intel’s subsidiary Mobileye is focused on the development of chips for autonomous driving. In the 2022 CES, Mobileye announced its next-generation SoCs for ADAS EyeQ6L, EyeQ6L, and EyeQ6H.
The L-version will be able handle levels 2 automated driving systems. It is expected to start production in the mid-year of 2023. The chip with the most power called EyeQ6H will be released in a little further (in 2024) and will offer more robust capabilities for ADAS.
As of the date of the writing of this article, Mobileye is working to BMW, Nissan, NIO, Volkswagen, Ford, and WILLER for the development of autopilot.
Tesla could have been the first brand to launch an infotainment system with functions similar to consoles however, we believe this trend will gradually extend to other car brands as well.
That’s right, the power of GPUs are expected to be required for all cars. For media, gaming, or other forms of entertainment or they will be utilized to aid in the development of an Autonomous driving system Level 5.
We expect any updates or improvements on the GPUs of cars to be included in this guide.