Graphics cards are an important aspect of any gaming PC build because they dictate the quality level that can be achieved from your monitor’s output data stream to the screen itself. In this buying guide, the usage of a graphics card is pretty different as we are finding the best GPU for deep learning.
Deep learning is a sort of AI or artificial-intelligence that has shaken up the tech world. Deep Learning systems are able to learn from data and improve their performance over time. This buying guide will take you through some of the best GPUs for deep learning so you can get started on projects.
Deep learning is an industry-changing technology that led to rapid innovation in every sector imaginable, including healthcare, finance, marketing, robotics, self-driving cars, and more. The true power of deep learning lies in its ability to learn from data continuously; it gets smarter with each new piece of information it processes.
Deep Learning has been a sizzling subject in the field of AI for some time now. However, it is only recently that GPUs have become powerful enough to make Deep Learning feasible on the desktop and gaming laptop. This article walks you through your options for the best GPU to buy if you are looking to get into Deep Learning with minimal hassle or expense.
Our recommended list of the Best GPU For Deep Learning
- HHCJ6 Dell NVIDIA Tesla K80 24GB GDDR5 PCI-E 3.0 Server GPU Accelerator
- NVIDIA Tesla P100 GPU Computing Processor
- Nvidia Tesla v100 16GB
- EVGA GeForce RTX 3080 Ti FTW3 Ultra Gaming
- NVIDIA Titan RTX Graphics Card
- NVIDIA TITAN V VOLTA 12GB HBM2 VIDEO CARD
1. HHCJ6 Dell NVIDIA Tesla K80 24GB GDDR5 PCI-E 3.0 Server GPU Accelerator
Computing becomes more powerful, faster in each given day—you need a reliable GPU capable of handling data-intensive workloads for your server. Make the upgrade without bothering with downtime or stopping your machine.
Fast enough to process complex simulations that outperform deep learning CPUs when processing large datasets, this NVIDIA Tesla K80 GPU is scalable from single to quad GPUs per node. Completely certified by Dell and powered by NVIDIA CUDA, solid-state graphics provide improved productivity and reliability through high-speed redundancy.
Get started before any deadlines are missed with blazing fast workflows paired with 24 GB of speedy GDDR5 memory. With the help of this graphics card, the process of deep learning will be much easier for the processor.
The new Nvidia Tesla K80 is a server-grade GPU that provides unmatched performance for supporting large computationally demanding enterprise applications for science, engineering, hyperscale data analysis, and simulation.
We have included the newest technology in the server field to bring you this next-generation machine learning tool with 4992 NVIDIA CUDA cores to help push massive amounts of data around without slowing down.
The 24 GB of GDDR5 brings heightened bandwidth so those compute-intensive jobs can be done with unparalleled speeds and processed as quickly as possible. The Tesla K80 is not your average GPU accelerator.
Smart enough to handle complex scientific computing and data analytics in a snap, this card is designed with the power of up to 8.73 teraflops behind it. The measurements of the product are 10.5 x 1.5 x 4.4 inches, and it weighs around 3.01 pounds.
2. NVIDIA Tesla P100 GPU Computing Processor
Tesla P100 is the world’s most advanced computing platform for high-performance computing or hyperscale data centers, powered by the NVIDIA Pascal GP100 GPU based on revolutionary new technologies. Tesla GPUs are well suited for applications in deep learning engineering and enterprise analytics.
The NVIDIA Tesla P100 GPU computing processor is a technical workhorse that unleashes the power of Tesla graphics-processing technologies in your PC.
The Tesla P100 delivers intense computational powers with its astounding 21 teraFLOPS and nine terabytes per second memory bandwidth, making it the world’s fastest compute node while significantly reducing downtime.
So get down to business with this Nvidia GeForce card-equipped device that doubles up cores for fast processing speed. Tesla P100 has taken innovation to new heights with more than ten times the performance compared to other GPUs in use today.
The Nvidia Tesla P100 is more than just a GPU. This product truly puts the perfectness with its revolutionary new architecture and unparalleled power efficiency.
That will change the way you compute for training neural networks and solving computational catalysis simulations. With a 16 GB memory capacity, this card achieves 21 teraflops of double-precision performance out of each node. This 16 GB graphics card has a 1 x 1 x 1 inch measurement, and it weighs 1 pound.
3. Nvidia Tesla v100 16GB
The Nvidia Tesla V100 is a hardware and software AI GPU processor designed to make graphical processing simpler. In addition, the GPU is lighter on power than many more traditional silicon products, which can be an important consideration for those designing sustainable data center operations.
The performance of this device will provide you with the graphics that meet your needs, all while reacting to changes in task demands without sacrifice. Designing sustainable data centers from the ground up is possible thanks to devices like the Tesla V100.
The Nvidia Tesla v100 is the latest GPU on the market to provide data scientists with the processing power they need for their work. The company makes a commitment to solving problems that are not simple, and this massive upgrade of the IT process will bring about improvements in healthcare, medicine, finance, engineering design, and more.
Dozens of deep neural networks and trillions of matrix multiplications can be processed quickly with the power of NVIDIA Volta’s leading-edge V100 Tensor Core GPU. Rise to new heights with Nvidia’s new Tesla V100 as 640 Tensor Cores power it.
The GPU delivers up to 100 teraFLOPS of deep-learning performance, making it the world’s most powerful computing server for AI. These NVIDIA NVLink powered servers are perfect for training a wide range of tasks from object identification and speech recognition to potential lifesaving driverless cars.
With this groundbreaking speed in processing times, we can now solve problems that were once thought impossible through artificial intelligence.
4. EVGA GeForce RTX 3080 Ti FTW3 Ultra Gaming
Game with the best EVGA GeForce RTX 3080 Ti graphics cards is also perfect for deep learning tasks. They feature the Real Boost Clock speed of 1800 MHz and a memory of 12GB of GDDR6X VRAM. This card has everything a consumer has been waiting for in a high-end gaming product. Cost-efficient? Absolutely.
The EVGA GeForce RTX 3080 Ti is a total steal at its sale price today, don’t wait to buy that addictive new game before it too gets marked down! Never settle for less when looking for your next high-quality GPU or video accelerator card; the most trusted cards like the EVGA GeForce RTX 3080 Ti are here.
With RTX, EVGA was the best company to provide deep learning and AI technology excellence in their graphics cards. And still leading the way with the exclusive RTX, TensorRT-accelerated Deep Learning Super Sampling, which extracts details from images that no other GPU can for seamless textures.
It also offers TriFAN cooling, nine thermal sensors for real-time temperature monitoring on key components, and an optional metal backplate with TORX3D Design for powerful durability with exquisite style. Triple Fans + 9 iCX3 thermal sensors give more powerful cooling and much more peaceful acoustic sound.
The power of NVIDIA Tensor Core GPU architecture with RT Cores provides next-generation artificial intelligence features in deep learning algorithms on this beast gaming card.
5. NVIDIA Titan RTX Graphics Card
The Titan RTX is the world’s most powerful graphics card a consumer can get for deep learning. It supports the newest Turing architecture and Tensor Cores so the user can enjoy amazing visuals in ray-tracing, deep learning neural networks, or mixed reality media to a brilliant next level.
Designed for NVIDIA GeForce RTX gamers and VR experiences that need extreme performance. This gaming GPU comes with 24 GB of GDDR6 memory running at 14 Gbps on an incredible 576-bit bus width while delivering up to 672GB/s of memory bandwidth.
The Titan RTX solids these unbelievable specs by integrating 72 RT cores for fast ray-tracing performance and 4608 CUDA cores clocked at 1770 MHz boosted clock speed. NVIDIA Titan RTX will make you cry over the beauty of its AI capabilities.
With the 24GB of GDDR6 memory, this graphics card will run flawlessly on your computer or deep learning laptop with at least a 650-watt power supply. Never worry about more demanding tasking slowing down your gameplay again because this graphics card will have them at ready-to-deliver speeds that will dazzle you as soon as they’re needed.
It also has deep learning features such as inference acceleration that make it perfect for revolutionizing innovation in industries from healthcare to science. With its Turing architecture, it’s capable not only of handling virtual reality but helping you program a zero-gravity remote robot that would take selfies for us without any rocket propulsion.
6. NVIDIA TITAN V VOLTA 12GB HBM2 VIDEO CARD
Powerful and Versatile for Machine Learning, NVIDIA’s latest GPU architecture is an exponential leap forward in performance. With 640 Tensor Cores that outperform its predecessor by 5x.
The new TITAN V VOLTA graphics card delivers the computational power required to accelerate a mix of critical tasks like machine learning training and some of the most computationally demanding deep neural networks available.
The TITAN is the world’s most powerful desktop GPU for various tasks. With 640 Tensor Cores, Volta conveys five-time progress in deep learning performance instead of preceding generation architecture. Superintendent for the latest computer, humanity’s most prominent difficulties will claim the power of this new GPU architecture.
The Volta NVLink GPU delivers tremendous performance for solving AI challenges with big data. The architecture of this GPU encompasses a broad range of hardware, software, and system capabilities, including the world’s fastest multi-precision floating point capability.
The NVIDIA TITAN is a 12GB Volta-optimized GPU that can help you discover data science insights faster than ever. This graphics card opens new possibilities with its mighty speed and power, from machine learning to solar cell modeling. The measurements of this GPU are 1 x 1 x 1 inches, and it weighs around 1 pound.
Best GPUs For Deep Learning Buying Guide:
If you’re looking for the best GPUs to power your deep learning and gaming experience, then we highly recommend NVIDIA. We have found that each of their products is top-notch with commendable specifications and features.
Although the GPU is optimized by needing an Artificial Intelligence app in gaming PCs or other deep learning apps, it is an example of good decisions. Picking the appropriate unit will guarantee that users will enjoy the deep learning and gaming activity without annoyances! Here are some of the more basic points that need to be noted before you do a purchase.
Memory is the most important part of a graphics card. If you plan on playing games at 1080p and above, make sure your graphics card has plenty to spare.
At least 6 GB or more will get you started; 8 GB for gaming machines is necessary. However, when it comes to deep learning or Artificial Intelligence applications, the required minimum VRAM is 6 GB and can perform better with more capacity.
Space is crucial for a gaming card. Make sure you have enough room in your case to accommodate the length, height, and thickness of graphics cards.
These GPUs come in different varieties depending on their size: slim-sized (half-height), single-slot, dual slots, or even triple slots (or more). If possible, look for mini versions of these cards as they can fit into smaller deep learning motherboards such as Z590 Mini ITX boards.
Thermal Design Power:
If you are looking to add a graphics card with an increased thermal design power, then it is recommended that the user also upgrades their PSU.
If your current PC has less than 600 watts of total output, and if you want to upgrade from an RTX 3080 Ti(or below) or 6800, specific power requirements will be more likely needed in order for them not to exceed TDP limitations.
All gaming cards require more than the basic maximum of 75 Watts that x 16 PCI-express slots offer. Many have 6- and 8-pin connectors in two or three varieties, depending on power supply compatibility.
You’ll want to upgrade if you don’t have supplemental connectors your card needs. Some with one connector, others with two or three ports depending on their needs. If your power supply doesn’t have ample additional connections, you need to accommodate this demand for quality graphics processing.