Graphics processing units (GPUs), are specialized processors used to speed up computations. GPUs, are found in all sorts of places, from custom gaming laptops to embedded computers found in drones and other flying machines. They are used in many applications such as machine learning, generative modeling, and computer graphics.
The GPU challenge - It's expensive! So, what’s the alternative?
GPUs are expensive as hell, especially when you couple them with the vast amount of memory they need. In fact, they are more expensive than high-end CPUs. So, how do keep up with GPU technology and avoid getting left behind?
There is a way to keep up with GPU technology and avoid getting left behind - Cloud GPU. The cloud GPU allows you to quickly add a GPU to your data centers at a low cost.
What is Cloud GPU, and the benefits of Cloud-based GPU
The cloud GPU platform allows users to access GPU resources as if they were on a local network for a cheap price. Cloud computing is popular with businesses as it is convenient and flexible. Cloud-based GPU computing offers the following benefits:
One can scale up or down within minutes, without incurring capital expenditures. The default data center is off-site and lies outside one’s office. Any computing demands can be met without even leaving the office walls.
Cloud GPU services provide more flexibility and consistency to customers by giving them access to all the GPU resources.
Cloud GPU services offer shared resources, thus reducing the capital needed to maintain the environment.
Companies that provide GPU computing services in the cloud
Some of the cloud service providers that offer GPU computing services are Amazon Web Services, Microsoft Azure, Google Cloud Platform, IBM SoftLayer, and Alibaba Cloud. They offer GPUs of various models, compute power, storage capacity, and price.
Amazon Web Services (AWS), Microsoft Azure, and Google Cloud are the top three commercial cloud providers. AWS offers a wide variety of GPUs in its G4 instance, including the Tesla V100 and the Tesla M60. Microsoft offers a single GPU instance in Azure, the Microsoft Azure G5. Google has a wide variety of GCP instances to choose from: such as G4, G7, and G8.
Amazon’s V100 can deliver up to 23 TOPs (teraflops) of performance and can support up to 448 GB/s of memory bandwidth. The company offers a managed service called Amazon Elastic Compute Cloud (Amazon EC2). EC2 allows customers to cluster their GPU instances in various locations such as the US East, US West, Europe, Asia Pacific, Middle East, Africa, and China.
One of the best cloud GPU providers is Paperspace. Paperspace offers a variety of features. The Paperspace platform is easy to use and customize, so you can build a render environment that meets your needs.
It also allows you to access your GPU from anywhere in the world. Paperspace offers a virtual desktop that allows you to launch your GPU servers on a single server in a matter of minutes.
In its cloud instances, Google Cloud provides a diverse choice of GPU servers. The virtual servers have been specifically designed to function with GPUs. You can easily launch these servers with a few mouse clicks and then begin running your demos and rendering projects. You can also scale it up and down as you wish.
You can pick from many different GPU instances, both for Linux and Windows. And, since Google Cloud offers containers and static websites, you can build a flexible render farm without a lot of extra work. Google Cloud offers Caffe, Tensorflow, and CUDA instances, which are all built on Nvidia GPUs. Besides, it offers flexible pricing, so you can pay only for the resources you need.
Oracle Cloud offers a wide range of GPU. You can choose from Oracle Caffe, TensorFlow, and CUDA instances, which are all built on NVIDIA GPUs. With Oracle Cloud, you can build a render farm. You can launch GPU instances with a few clicks and scale your server up and down as needed.
Microsoft is always innovating to improve, accelerate, and enhance the reliability of its cloud computing services. In its cloud instance series, Microsoft Azure provides a diverse range of GPUs. In its NCv3 instance series, it offers the NVIDIA Tesla V100 and the T4 GPU with AMD EPYC2 processor.
Ushering in a new era for high-performance computing, LeaderGPU provides powerful GPU instances. LeaderGPU is built on Spark and Kubernetes and is optimized for GPU-powered applications. LeaderGPU offers NVIDIA Tesla K80, NVIDIA Tesla V100, and NVIDIA Tesla M60. LeaderGPU also provides additional performance enhancements and services to provide optimal customer experience. LeaderGPU provides servers specifically designed for machine learning and deep learning purposes. LeaderGPU Includes development tools based on the programming languages Python 2, Python 3, and C++.
Cloud GPU providers offer flexible pricing, increased availability, and a wider range of GPU instances. Amazon, Google, Oracle, and Microsoft are some of the major cloud GPU providers.