Instead of concentrating on solely video and gaming, GPU technology is currently being used in a wide range of industries, including banking, healthcare, machine learning, data science, and other emerging industries like crypto mining. Since businesses are moving away from on-premise infrastructure, it is crucial that it can be used in the cloud for accessibility.
It can be challenging to determine which cloud providers give the greatest GPU service, but we’ve found that Runpod and Linode are the best out of all these GPU services.
What is a GPU?
Although CPUs are more commonly known, GPUs are renowned for being a crucial part of providing excellent graphics in gaming systems and graphics-intensive apps. GPUs are now commonly utilized in artificial intelligence and machine learning to handle large amounts of data used in model training.
Like the CPU, the GPU is a silicon-based computer that speeds up the production of graphics by modifying and manipulating the memory. GPUs perform their computing in parallel, in contrast to CPUs, allowing them to perform complex computer tasks simultaneously.
The rendering of high-quality visuals for video games and the intense data point processing necessary for data science and developing machine learning models both depend on this high computational performance.
Who uses Cloud GPU Services?
Many businesses use GPUs for their compute-intensive applications and workloads in native IT infrastructures. GPU technology is rapidly evolving, and NVIDIA—one of the largest GPU suppliers—releases a new GPU virtually every year. This is typical of many technological stacks. In addition to being challenging, keeping up with this rapidly evolving technology is also quite expensive.
However, as more businesses move their IT infrastructure to the cloud, cloud service providers can keep up with advances in GPU technology and offer them to these businesses at a lower price than on-premise.
Numerous GPU cloud providers exist, including well-known cloud service providers. They all provide GPUs in various models, with varying processing, storage, and pricing levels.
In this article, let’s take a look at some of the best.
Best Cloud GPU Services
Runpod
RunPod is committed to providing a top-notch user experience in the realm of GPU computing. Our platform offers container-based instances that can be quickly and easily spun up, as well as custom bare-metal and virtual machine deployments.
In the future, they plan to offer automated on-demand virtual machines in the fourth quarter of 2022, and aim to introduce serverless GPU compute shortly after that. With our cutting-edge technology and commitment to customer satisfaction, RunPod is a leader in the field of GPU computing.
Runpod.io offers a range of services to help users automate their workflow and take advantage of cloud GPU technology. Their platform allows users to spin up GPUs on demand or use Spot GPUs to save on costs.
One of the key features of the platform is the ability to access GPUs through a CLI or GraphQL API. This allows users to easily integrate their services into their existing workflow and spin up GPUs within seconds. Additionally, they offer OnDemand and Spot GPUs, giving users the flexibility to choose the option that best fits their needs. OnDemand GPUs provide consistent reliability without interruptions, while Spot GPUs can save users up to 50% in cost for jobs that can tolerate interruptions.
In addition to the CLI and API, RunPod also offers multiple access points for users to connect to their GPUs, including SSH and TCP ports, as well as HTTP ports. This allows users to easily code, optimize, and run their AI and ML jobs on the platform.
Finally, they offer persistent volumes, allowing users to stop and resume their pods while keeping their data safe. This means users can pause their computations and pick up where they left off at a later time, without losing any of their data.
Overall, runpod.io provides a powerful and flexible platform for users to take advantage of cloud GPU technology and automate their workflow.
RunPod is already being used by a number of users to run blender workloads. They have reported speed-ups in their render cycles of up to 100 times when compared to the single-GPU desktop PCs they were utilizing in the past because rendering is extremely parallelizable.
Linode
For parallel processing tasks including video processing, scientific computing, machine learning, AI, and more, Linode offers on-demand GPUs.
It offers GPU-optimized virtual machines (VMs) that are powered by NVIDIA Quadro RTX 6000, Tensor, and RT cores, and it makes use of the CUDA power to run the complicated computation, deep learning, and ray tracing applications.
By utilizing Linode GPU access, you can convert your capital investment into an operating expense while maximizing the true value of the cloud. Additionally, Linode enables you to focus on your key talents rather than worrying about the hardware.
With Linode GPUs, it is now possible to use them for sophisticated applications like video streaming, artificial intelligence, and machine learning. In addition, depending on the amount of processing power required for anticipated workloads, you may receive up to 4 cards for each instance.
4,608 CUDA cores, 576 Tensor cores, 72 RT cores, 24 GB of GDDR6 GPU memory, 84T RTX-OPS, 10 Giga Rays/sec Rays Cast, and 16.3 TFLOPs of FP32 performance are all features of the Quadro RTX 6000.
The dedicated + RTX6000 GPU plan costs $1.5 per hour.
Amazon AWS Web Services
Amazon offers a variety of GPUs in its P3 and G4 EC2 instances, making it one of the first major cloud providers to offer GPU cloud service. The Tesla V100 GPU, one of the most popular NVIDIA GPUs offered by many cloud providers, is available in Amazon’s P3 instance.
It has 16 GB and 32 GB variants of VRAM per GPU. There are two different kinds of G4 instances: G4dn, which uses NVIDIA T4 GPUs with 16GB VRAM, and G4ad, which uses more potent AMD Radeon Pro VS20 GPUs with 64 vCPUs.
Depending on the GPU instance you choose, AWS permits clustering several GPU instances utilizing the x-large instance sizes, which are available in the US East, US West, Europe, Asia Pacific, Middle East, Africa, and China regions.
Paperspace
One of the leading cloud-dedicated GPU providers, Paperspace has a virtual desktop that enables you to quickly launch your GPU servers.
There are four different GPU cards available, starting with the P4000 GPU with 8GB VRAM for $0.51 per GPU/hour, followed by the P5000 GPU with 16GB VRAM for $0.78 per hour, the P6000 dedicated GPU with 30GB VRAM for $1.10 per hour, and the potent 16GB NVIDIA Tesla V100 GPU for $2.30 per hour, which is best for a variety of intensive tasks.
With its P5000 x 4 and P6000 x 4 GPUs, which are provided at $3.12 and $4.40 per hour, respectively, Paperspace also provides numerous GPU clusters.
Google Cloud Platform
Google Cloud provides a variety of GPU servers in its cloud instances so that you can execute your resource-intensive apps.
At $2.48 and $0.45 per hour, respectively, it provides the well-known NVIDIA V100 GPU with 16GB GPU RAM and 900GB/s bandwidth as well as the Tesla K80 with 12GB VRAM and 240GB/s bandwidth.
The NVIDIA Tesla P100 (16GB VRAM, 732GBps bandwidth, $1.46 per GPU/hour), T4 (16GB VRAM, 320GBps bandwidth, $0.35 per GPU/hour), and P4 (8GB VRAM, 192GBps bandwidth, $0.6 per GPU/hour) are additional GPUs that are accessible through Google Cloud.
The Tesla T4 GPU from Google Cloud is a multifunctional GPU with excellent bandwidth and efficiency that can be utilized for many high-end tasks at a cheap cost per hour.
The US central region often has access to the T4 and other GPUs (Lowa). Depending on your chosen model, Google cloud GPUs are accessible in the US East, US West, North America, South America, Europe, and Asia. The US West includes Oregon, Los Angeles, Las Vegas, and Salt Lake City.
Vast.ai
Through the marketplace Vast.ai, both public and private users can rent out their unused GPU resources.
You may obtain a Tesla V100 GPU with 16.2GB GPU RAM and 71.45GB/s bandwidth for about $0.85 per hour in the Texas US region, one of the many unique cloud GPUs that are accessible in various locations across the world.
In addition, cloud GPU models like the GTX 1080, RTX 3090, and Quadro P5000 are all reasonably priced when compared to other big cloud service providers.
Oracle Cloud
Oracle Cloud provides three NVIDIA GPU models: the popular Tesla V100 GPU with 16GB VRAM and 4GBps bandwidth for $2.95, the more potent NVIDIA A100 GPU with 40GB VRAM and 12.5GBps bandwidth at $3.05 per GPU/hour, and the Tesla P100 16GB VRAM with 25GBps bandwidth at $1.27 per hour.
Oracle is the first company to provide the A100 GPU with double the RAM and significantly more local storage.
Additionally made available on virtual machines, Oracle cloud GPUs such as the NVIDIA Tesla Volta V100 and P100 can be used in the London (UK), Ashburn (US), and Frankfurt (Germany) regions.
Microsoft Azure
A variety of GPUs is available in Microsoft Azure’s cloud instance series. Its NCv3 instance series includes the T4 GPU with AMD EPYC2 processor and the NVIDIA Tesla V100, both of which are available for $2.95 per hour.
At $0.87 per GPU/hour, it also provides the Tesla M60, Volta V100, and K80 GPU. One of the most potent GPUs available through Microsoft Azure is the AMD Radeon Instinct M125 GPU, which exclusively supports Windows OS.
Virtual machines and GPUs from Microsoft Azure are often offered in the regions of northern Europe, the US West, and South Central America.
Leader GPU
A complete platform for renting cloud GPUs is called LeaderGPU. Depending on your use case and time commitment, it makes a wide range of GPUs available.
The NVIDIA Tesla Volta V100 (16GB GPU RAM, 900Gbps bandwidth), Tesla P100 (16GB GPU RAM, 720Gbps bandwidth), RTX 3090 (24GB GPU RAM, 936ps bandwidth), Tesla T4 (16GB GPU RAM, 320Gbps bandwidth), and GTX 1080 are among the GPU variants it offers (8GB GPU RAM, 320Gbps bandwidth).
These GPU servers are mostly available as many GPUs, such as the 8 x GTX 1080Ti for €108.3 per day and the 6 x Tesla T4 for €90.71 per day.
IBM Cloud
In its GPU cloud instances, IBM Cloud provides three NVIDIA T4 GPUs with 32GB of GPU RAM, but different Intel Xeon processors. At $819 a month, the T4 GPU with an Intel Xeon has 20 CPU cores. The Intel Xeon 5218 T4 GPU with 32 cores is available for $934/month, and the Intel Xeon 6248 T4 GPU with 40 cores is available for $1,704/month.
Several data centers, including those in the US, Canada, the EU, and Asia regions, provide IBM Cloud GPUs.
Additionally, they provide 4 different AC virtual GPU servers starting at $1.95/hour.
Alibaba Cloud
The GA1, GN4, GN5, GN5i, and GN6 instance types are the five GPU instance versions that Alibaba Cloud offers. The GA1 instances offer up to four AMD Fire Pro S7150 GPUs with 32GB of GPU RAM, while the GN4 instances offer an NVIDIA Tesla M40 GPU with 24GB of GPU memory. The GN5, GN5i, and GN6 instances, meanwhile, offer the Tesla P100 (128 GB, max 8x), P4 (16GB VRAM, max 2x), and Tesla V100 (128GB GPU memory), respectively.
Tencent Cloud
Cloud GPU services are one of the many cloud solutions offered by Tencent Cloud, a cloud platform. It provides a variety of NVIDIA GPU instances designed for heavy computing.
The Tesla V100 with 32GB VRAM is available with NVLINK in the Tencent Cloud GN10 instances, the Tesla M40 GPU is available with the GN2 instance, the Tesla P40 GPU is available with the GN6 instance, and the Tesla T4 GPU is available with the GN7 and GN7vw NVIDIA GPU instances.
Instances of the Tencent Cloud GPU are accessible in Asia, including Silicon Valley, Guangzhou, Shanghai, Beijing, and Singapore.
To find the availability zone nearest to your location, you would need to visit the Tencent cloud website.
What GPU cloud service should I select?
Our favorite GPU cloud services are Linode and Runpod. The others on this list will get the job done, but we suggest using either of these cloud services.
However, as a general rule, you should pick a cloud GPU provider based on your spending limit and the availability in your neighborhood (because this affects price). When selecting the GPU instance or model you’ll be using, other factors will be relevant.
Nearly all cloud providers provide the extremely potent NVIDIA Teslas V100 GPU, which is ideal for running intense computational tasks like machine learning, advanced graphics rendering, and 3D applications.
Use the Tesla if your application requires a lot of GPU processing power, but be sure to shop around for the best deal. For the V100 GPU’s great speed and dependability, Paperspace charges a rather reasonable price.
Another potent GPU that is less expensive than the Tesla V100 is the Tesla K80. It works best for training some card programs, mid-level machine learning models, and high-definition video rendering.
Every GPU model is created for a specific use case, and the cost varies from a cloud platform to cloud platform.
Final Thoughts
If you want the best experience, computing power, and capabilities while using a Cloud GPU service, then go with Runpod or Linode.
The customer service is quick and easy, making these two services our top contenders.
You won’t be disappointed!