NVIDIA Titan RTX : Specifications, Architecture, Working, Differences & Its Applications

The NVIDIA Titan RTX from the NVIDIA Titan series was released and announced in late August 2018. After that, the card went on sale in the USA in late December 2018. The Titan RTX is a professional-grade product due to its price at approximately $2,499, which also holds the name of the fastest PC gaming GPU worldwide at the time. This article elaborates on NVIDIA Titan RTX, its working, and applications. The NVIDIA Titan V is the predecessor of the Titan RTX. The Titan RTX was a part of the GeForce RTX 20 series generation, which incorporates the latest hardware for RT cores in addition to the Tensor cores. This article elaborates on Titan RTX, its working, and its applications.

What is NVIDIA Titan RTX?

The TITAN RTX was an enthusiast-class graphics card by NVIDIA, based on the TU102 graphics processor with the 12 nm process. This card supports DirectX 12 Ultimate in its TU102-400-A1 variant. This ensures that all current games will work on TITAN RTX. In addition, the support of DirectX 12 Ultimate guarantees support for variable-rate shading, hardware ray-tracing, and more in future video games.

The TU102 is a large chip with 754 mm² & 18,600 million transistors die area. It features shading units – 4608, texture mapping units – 288, and ROPs – 96. In addition, it features tensor cores – 576, which enhance the speed of ML applications. This card can also have raytracing acceleration cores – 72. NVIDIA has connected 24 GB of GDDR6 memory with the TITAN RTX through a 384-bit memory interface. Therefore, the GPU operating frequency ranges from 1350 MHz to 1770 MHz, and runs at 1750 MHz.

The NVIDIA TITAN RTX is a dual-slot card that draws power from two 8-pin power connectors, with a maximum 280 W of power draw. In addition, it can also have display outputs like an HDMI 2.0, three DisplayPort 1.4a, and USB Type-C. This GPU is connected using a PCI-Express 3.0 x 16 interface to the remaining system.

NVIDIA Titan RTX Working Principle

The NVIDIA Titan RTX works based on its Turing architecture, which introduced a hybrid rendering model with specialized and dedicated cores for separate tasks. This architecture features CUDA cores used for general parallel processing, Tensor Cores used for AI acceleration, and RT Cores for real-time ray tracing.

The Titan RTX GPU works as a specialized high-performance computing tool. Therefore, it incorporates AI acceleration, real-time ray tracing, and general parallel processing into a single desktop GPU, aimed at AI researchers, content creators, and developers. The combination of these architectural components will allow major speedups for demanding professional applications. This architecture will make it a versatile tool in AI research, content creation, and data science for professionals.

Specifications

The NVIDIA Titan RTX specifications include the following.

• It is a high-end PC GPU (graphics processing unit).
• It is built on the NVIDIA Turing architecture
• It features a TU102 GPU.
• CUDA Cores – 4,608
• Tensor Cores – 576
• RT Cores – 72
• Boost Clock is 1770 MHz
• Base Clock is 1350 MHz
• Memory is 24 GB GDDR6
• Memory Interface is 384-bit
• Memory Bandwidth is 672 GB/s
• AI Performance is 130 TFLOPS
• Single-Precision Performance is 16.3 TFLOPS
• Ray-Tracing Performance is 11 GigaRays per second
• Thermal Design Power or TDP is 280W
• Recommended PSU is 650W
• Video Outputs like HDMI, DisplayPort 3, and a single USB-C.
• NVIDIA NVLink helps in connecting two TITAN RTX GPUs
• NVIDIA NVLink BW is 100 GB/s.
• System Interface PCI Express is 3.0 x 16.
• Power Consumption is 280 Watts.
• Thermal Solution is active
• Form Factor (H x L) is 4.4 x 10.5.

NVIDIA Titan RTX Architecture

The NVIDIA Titan RTX GPU is built on the Turing architecture with CUDA cores – 4608, Tensor Cores – 576 for AI acceleration, and RT Cores – 72 for real-time ray tracing. In addition, it can also feature GDDR6 memory – 24 GB with the support of CUDA-X AI SDK for optimizations of performance. This GPU delivers AI performance up to 130 Tensor TFLOPS and real-time ray tracing up to 11 GigaRays per second. This architecture can also support NVLink for multi-GPU.

Components

The NVIDIA Titan RTX Architecture can be built with different components like GDDR6 memory, RT Cores, CUDA Cores, Tensor Cores, NVLink, Display Outputs, vapor chamber, VirtualLink connector & NVLink bridge. This architecture’s components are discussed below.

GDDR6 Memory

The NVIDIA Titan RTX architecture uses high-speed GDDR6 memory – 24 GB with a 384-bit memory interface & memory bandwidth – 672 GB/s. This memory was critical for the card’s target audience of data scientists, content creators, and AI researchers by allowing them to manage huge datasets & complex workloads. This setup provides significant memory throughput to keep up with the demands of the Turing architecture’s processing cores, like the RT Cores and Tensor Cores.

RT Cores

The NVIDIA Titan RTX features dedicated hardware units like RT Cores – 72, which can be built into the Turing architecture for speeding up real-time ray tracing. These cores are responsible for simulating the physical performance of light to make photorealistic graphics in real-time by delivering up to 11 GigaRays per second on this graphics card. Therefore, this makes the graphics card powerful for AI researchers and creative professionals who require rendering complex visual scenes & workloads.

CUDA Cores

The Titan RTX GPU features basic processing units like CUDA cores – 4,608, which are 32-bit floating-point processors, designed for parallel computation and accelerate AI, scientific simulations, graphics rendering, and machine learning tasks. Generally, the maximum number of CUDA cores can lead to superior performance for parallelizable workloads.

Tensor Cores

The NVIDIA Titan RTX architecture features specialized hardware units like Tensor Cores – 576. They accelerate the tensor and matrix operations by delivering up to 130 teraflops of performance. So these are essential to scientific computing, AI, and deep learning workloads. These cores can perform mixed-precision calculations with half-precision FP16 for multiplication & single-precision FP32 for accumulation. Therefore, it significantly enhances performance for neural network training & inference tasks without a large accuracy loss.

NVLink

The NVLink in this architecture is used to connect two well-matched GPUs by letting them group their memory & converse at a high-speed and high-bandwidth interconnect. Therefore, this allows total memory up to 48 GB for demanding tasks like professional ray tracing and AI research by providing significant performance increases over only a PCIe connection and a single GPU.

Display Outputs

The NVIDIA Titan RTX has five display outputs like DisplayPort 1.4 – 3, HDMI 2.0b – 1, and a USB Type-C port – 1 that supports the VirtualLink standard. This combination will allow for single-cable connectivity and multi-monitor setups to next-generation VR headsets that utilize the VirtualLink port. It includes three DisplayPort 1.4 connectors, one HDMI connector & one USB Type-C connector (VirtualLink).

• The DisplayPort 1.4a supports refresh rates and high resolutions like 8K at 60 Hz from a single link.
•  HDMI 2.0b is a standard audio interface and digital video.
• USB Type-C port is dedicated to VirtualLink, which is a next-generation standard for VR headsets that merges display, power & high-speed data into a single cable.

Cooling

The cooling system in this architecture features double 13-blade fans, a larger vapor chamber, and a dual-slot design. These fans can improve airflow by 3x, whereas the vapor chamber spreads heat efficiently to the fin stack to make it appropriate for demanding workloads.

• The two 13-blade fans in this architecture produce three times the airflow as compared to earlier models while keeping quiet operation.
• A full-card vapor chamber is a key component of the cooling solution that is double as large as earlier versions, increasing heat spreading & transfer to the heat-sink fins.
• This graphics card features a dual-slot cooling solution, so it occupies dual expansion slots within a computer case.
• A dual-fan cooling system can be implemented to manage the generated heat in intense workloads.

Software System

The NVIDIA Titan RTX GPU leverages a complete software system that is built on the CUDA-X AI SDK & other developer tools. So it allows AI research, content creation, and high-performance computing. This software system can be designed to connect the specialized cores of GPUs very effectively. Basically, the software system for the Titan RTX is not a single OS (operating system) or application, although it has a strong ecosystem of drivers, platforms, and SDKs. So it allows high-performance computing tasks across different research and professional fields.

How to Maintain NVIDIA Titan RTX?

The steps involved in maintaining NVIDIA Titan RTX include the following.

• The NVIDIA Titan RTX can be maintained by keeping it very clean.
• Sometimes, it is essential to perform a deep clean when needed.
• Make sure the software drivers are up to date with the NVIDIA App.
• Utilize the NVIDIA control panel to improve its settings for your particular needs.
• Physically remove dust for deep cleaning from the fans & heatsink.
• Ensure the right airflow within your case.

NVIDIA Titan RTX Vs NVIDIA GeForce RTX 3090

The difference between NVIDIA Titan RTX and NVIDIA GeForce RTX 3090 includes the following.

Advantages

The advantages of NVIDIA Titan RTX include the following.

• It provides better performance for professional data science and AI research workloads.
• It also provides outstanding performance for high-end creative tasks like 3D rendering, real-time 8K video editing, scientific visualization, and many more.
• The 24GB of VRAM is perfect for large neural network training and big datasets processing that would be uncontrollable on lower-capacity cards.
• Dedicated Tensor Cores speed up AI workloads with support for various precision levels, which leads to quick training and inference.
• It can speed up data analytics with RAPIDS, a suite of open-source libraries that integrate with popular data science workflows.
• User connects two Titan RTX graphics cards with NVLink to double the memory to 48GB for the most demanding tasks.
• It enables researchers to imagine large datasets with responsiveness

Disadvantages

The disadvantages of NVIDIA Titan RTX include the following.

• Its price is extremely high.
• It needs significant cooling challenges within multi-GPU configurations.
• This GPU delivers poor performance where high double-precision capabilities are required.
• The Titan RTX was slightly faster, only for gaming by around 5 to 10%.
• The axial fan exhausts heat into the computer case instead of out the back because of the style design.
• These cards overheat quickly and turn on thermal throttling while used within multi-GPU setups. Thus, it can lead to a 60% performance drop.
• Effective use of several Titan RTX cards frequently needs a custom liquid-cooling system, which adds further complexity and cost.
• This card demands a high-end system to avoid bottlenecks and supply adequate power, adding to the overall system cost.
• The Titan RTX GPU has poor double-precision floating-point capabilities. Therefore, it limits its effectiveness within certain scientific & engineering simulations.

Applications

The NVIDIA Titan RTX applications include the following.

• The Titan RTX is designed for AI developers and researchers by enabling NN inference and faster training.
• It speeds up data analytics with RAPIDS tools by integrating with regular data science workflows.
• The 24GB of VRAM is essential for processing large datasets and training NNs with better batch sizes.
• It is compatible with memory-intensive 3D content creation & animation by providing the computational power required for complex models & scenes.
• This card handles real-time 8K video editing & other memory-intensive video workflows through GPU-accelerated effects.
• It is used for designing large-scale models in product and architectural design.
• The Titan RTX is used for research and scientific visualization that needs major GPU compute power.
• It provides the high performance required for running and developing VR/AR applications.
• It is the fastest gaming GPU, used for gaming at maximum settings.

In summary, the NVIDIA Titan RTX GPU was a powerful and niche GPU. This graphics card can serve as a crossover product between professional workstation cards and consumer graphics cards, mainly targeted at data scientists, content creators, and AI researchers. Here is a question for you: What is NVIDIA Titan X?