Fully Managed Cloud Solutions to Power Your Business
Agilesoft Cloud is self-developed and provides the essential IT infrastructure resources such as computing, storage, network and security.
Agilesoft Cloud is self-developed and provides the essential IT infrastructure resources such as computing, storage, network and security.
Cloud computing is an ever-changing art form more than a technology. We think big, listen well, and craft it gently. Our development team will keep working on the R&D to meet the market needs, and we’d love to surprise our customers with new insights and products.
Bare Metals offers you the benefit of the outstanding, undivided CPU power and performance of a dedicated server with 100% bandwidth without noisy neighbors.
Harness blazingly-fast, state-of-art cloud infrastructure that gives you unmatched computing power, simplicity and scalability for every need.
Your data security is always a priority to us. Our Global Private Network solution is a private infrastructure that is completely separated from the open Internet.
The ultimate hierarchy-free, S3 API compatible, and highly redundant multi-AZ object storage for your web app development, hosting files, storing backups, and much more.
Agilesoft empowers you with the robust frameworks, efficient workflows, and scalable infrastructure you need to build and deploy AI applications at speed. Start training your models on NVIDIA DGX™ H100 for just $2.79/hr
Engineers and scientists across various domains can leverage the NVIDIA H100 to accelerate AI inference workloads, such as image and speech recognition. The H100's powerful Tensor Cores enable it to quickly process large amounts of data, making it perfect for real-time inference applications.
The NVIDIA H100 Tensor Core GPU offers a diverse range of use cases for deep learning on larger models. The H100 revolutionizes deep learning for data scientists and researchers, allowing them to handle large datasets and perform complex computations for training deep neural networks.
One of the lesser known applications of modern GPUs is machine learning. Machine learning is a form of data analysis that automates the construction of analytic models. In essence, machine learning involves systems that use data to learn, identify patterns and make decisions independent from human input. Due to the highly resource-intensive nature of machine learning, GPUs are an essential component.
Considered a building block of artificial intelligence, machine learning is a computationally demanding process as it necessitates the input of large volumes of data for analysis. This analysis is performed by software known as machine learning algorithms. These algorithms then build models based on what is called training data or sample data. The resulting models are then used to form predictions or make decisions without any need for human input. This methodology has seen widespread implementation in fields ranging from medicine to email filtering, making machine learning a crucial yet frequently overlooked aspect of modern data infrastructures.
While 3D graphics are commonly used for video games, they have also become increasingly used in other forms of media such as films, television shows, commercials, and digital art displays. Similar to video editing, the creation of high-resolution 3D graphics can be a resource intensive and time-consuming process, even with state-of-the-art hardware.
Modern film studios often depend on GPU technology to generate ever increasingly lifelike and dynamic computer images, making the hardware a vital part of the movie-making process. Digital artists employ GPU-enabled computers to create abstract displays that could not be created in physical space, allowing them to create works of art unlike anything seen before. With the proper combination of hardware performance and artistic vision, GPUs can be a powerful creative resource for any media operation.
One of the more publicized uses of GPUs alongside gaming is their role in what is referred to as cryptocurrency mining or mining. The act of cryptocurrency mining involves the dedication of system resources to what is referred to as a blockchain, or a continuous record that uses sophisticated encryption algorithms to store transaction data. Each entry in this record is referred to as a block and requires a certain amount of computing power to generate.
While blockchain technology has uses outside of cryptocurrency, blockchains are generally involved in mining. This is most commonly seen in the context of the Bitcoin cryptocurrency, but blockchains exist for other currencies as well and the mining process can differ depending on the currency in question.
When it comes to mining Bitcoin, the process involves the dedication of hardware resources to the creation of blocks in the Bitcoin blockchain. The more blocks added to the blockchain, the more Bitcoin is generated. This comes at the cost of system resources and electricity, making efficiency key when engaging in cryptocurrency mining. The high throughput and relatively low energetic requirements of GPUs makes them uniquely suited to performing these high-demand tasks.
