Which GPUs Can Our Solutions Support? Comparisons and Use Cases


Source: NVIDIA

Many computers are equipped with GPUs (graphics processing units) that help take on complex tasks like graphics rendering and artificial intelligence, primarily due to their ability to divide up and process workloads among many cores. 

In this blog, you’ll learn about the different GPUs our systems can support, their main features, and the applications that these GPUs are best suited for.

First, let’s recap real quick what a GPU is. 

What is a GPU, and what is its purpose?

Invented by NVIDIA in 1999, the GPU is a processor that is made up of many smaller and more specialized cores than a CPU. 

Originally used for graphics and video rendering, over time they became more flexible and programmable, making them increasingly useful to accelerate workloads for artificial intelligence (AI) and high-performance computing

A GPU delivers massive performance when a complex task can be divided up and processed across its many cores. This allows for parallel processing, or the completion of multiple tasks simultaneously. 

Some other key manufacturers of GPUs include Intel and AMD (Radeon)

Which GPUs can our solutions support?

Our solutions are able to support many GPUs across various form factors and use cases. 

Some popular choices of GPUs our customers integrate into our systems are the NVIDIA RTX A4000 to A6000 series actively cooled GPUs. 

These processors are equipped with NVIDIA Ampere Architecture-based CUDA Cores, Second-Generation RT Cores, and Third-Generation Tensor Cores. These cores help greatly enhance the processing power of our systems across a wide variety of applications. (More on that later.) 

The CUDA Cores greatly accelerate graphics workloads for twice the performance of the previous generation. 

The RT Cores produce more visually accurate renders faster with hardware-accelerated ray tracing and motion blur for, once again, twice the performance of the previous generation. 

The Tensor Cores boost AI and data science model training performance with support for TF32 prevision and structural sparsity while bringing advanced capabilities to graphics workloads. 

Let’s take a look at three of the most popular in this series: 

RTX A4000

The NVIDIA RTX A4000 is the most powerful single-slot GPU for professionals, delivering real-time ray tracing, AI-accelerated compute, and high-performance graphics right to your computer. 

The A4000 is a single-wide (single-slot) GPU, which means that it only takes up one PCIe slot, allowing for more real estate within the system to assign additional PCIe cards or A4000 GPUs. 

Equipped with 6,144 CUDA Cores, 192 Tensor Cores, 48 RT Cores, and a max power consumption of only 140W, these GPUs allow for enhanced computing accuracy and reliability. 

16GB of GDDR6 memory (Sixth Generation Graphics Double Data Rate, used for fast rendering on GPUs) with ECC (error correction code memory) enable users to drive graphics and compute intensive workloads. 

With PCIe Gen 4, the A4000 allows users to improve data transfer speeds from CPU memory for data-intensive tasks. 

RTX A4000 GPUSource: NVIDIA. The NVIDIA RTX A4000 is the most powerful single-slot GPU for professionals, delivering real-time ray tracing, AI-accelerated compute, and high-performance graphics right to your computer. 

RTX A4500

The NVIDIA RTX A4500 allows users to harness the power of real-time ray tracing, simulation, and AI right from their computer. 

The A4500 is a double-wide (double-slot) GPU, which means that it takes up two PCIe slots, which are the most common types of GPUs these days. 

This GPU has 7,168 CUDA Cores, 224 Tensor Cores, 56 RT Cores, and a max power consumption of 200W, supercharging rendering, AI, graphics, and compute tasks.

With 20GB of GDDR6 memory with ECC, users can tackle memory-intensive workloads ranging from virtual production to engineering simulation. 

The A4500 also comes equipped with PCIe Gen 4 for increased data transfer rates. 

RTX 4500 GPUSource: NVIDIA. The NVIDIA RTX A4500 GPU allows users to harness the power of real-time ray tracing, simulation, and AI right from their computer. 

RTX 6000

The NVIDIA RTX A6000 delivers everything designers, engineers, scientists, and artists need to meet the most graphics and compute-intensive workloads.

Like the RTX A4500, the RTX A6000 is a double-wide GPU. With 10,752 CUDA Cores, 336 Tensor Cores, 84 RT Cores, and a max power consumption of 300W, this processor is equipped for unprecedented rendering, AI, graphics, and computer performance. 

48 GB of ultra-fast GDDR6 memory, scalable up to 96 GB, gives data scientists, engineers, and creative professionals the large memory necessary to work with massive datasets and workloads like science and simulation. 

With PCIe Gen 4, the A6000 provides double the bandwidth of the previous generation, increasing data transfer rates for data-intensive tasks like AI and data science. 

RTX A6000 GPUSource: NVIDIA. The NVIDIA RTX A6000 delivers everything designers, engineers, scientists, and artists need to meet the most graphics and compute-intensive workloads.

What applications are these GPUs best suited for?

AI-powered GPUs, like the NVIDIA A4000 to A6000 series, can be used in a variety of applications such as radar, C6ISR, JADC2, signal intelligence (SIGINT), electronic intelligence (ELINT), and communications intelligence (COMINT). 

These GPUs help process and interpret data within a matter seconds, allowing warfighters to gain a clearer understanding of their surroundings; it can also potentially be used to determine an adversary’s next moves. This will empower military personnel to stay ahead of enemy threats and respond within a matter of seconds. 

These GPUs, in addition to the RTX 3060 to RTX 3090 series GPUs, accelerate graphics workloads and produce highly accurate visual renders, making them ideal for a variety of gaming applications as well, but the RTX 3060 to RTX 3090 series are not geared towards rugged applications or high-demand data centers. 

What features do our customers focus most on?

When evaluating a GPU for integration into one of our systems, customers focus primarily on three things: memory, core count, and power consumption. 

The higher the memory and core count, the more likely the processor is able to handle tasks that involve vast amounts of data that need to be retrieved and analyzed within a matter of seconds.

GPUs with lower levels of power consumption reduce the risk of overheating, decreasing the risk of functionality issues and/or damaging a computer’s other critical components. 

For instance, the A4000 is a very popular GPU because it has great performance (high memory and core count), has a max power consumption of up to 140W, and is a single slot GPU, allowing for the addition of other components into a system. 

Compatible with the A4000 and other high core count GPUs, our systems help increase throughput and data analytics capabilities, enhancing situational awareness and, as a result, decision-making in real-time for military, commercial, and industrial applications. 

Conclusion

GPU technology is ever-expanding, with many industries utilizing the processing capabilities of GPUs in addition to CPUs.

Applications have become so complex that it may not be enough for a specific application to solely depend on CPUs; enhanced data analytics and graphics rendering are increasingly important to equip solutions with the most advanced compute power. 

One of Intel’s latest products, for example, is the Arc GPUbuilt for consumer high-performance graphics, including premium creative, gaming, and streaming services. 

In the future, there will be plenty of new integrations with next generations of PCIe technology and requirements for more dense computing. 

If you’d like to learn more about how we can help you create a customized solution with the latest GPUs, just reach out here.

We’d be more than happy to help. 





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