Dedicated GPU

Achieve Ultra-High Performance

High-performance Accelerators for Cloud Servers Parallelizing Computations Suitable For Parallel Processing, Machine Learning & Graphics-Intensive Applications.

  • Video Graphic Processing
  • Deep Learning
  • Parallel Processing
  • Gaming
Save Cost

Reduction in capital cost high purchasing and maintaining costs of GPU are minimized for better leveraging IT budget.

Market Leading Hardware

Powered by NVIDIA T4, a high-rating GPU with considerable CUDA, Tensor and RT Cores for parallel processing.

Image Processing Capabilities

According to GeekBench, the Gaussian Blur and Depth of Field Performance Score are 102,644 and 302,959 respectively.

Application Scenarios

Video/Graphics Processing
Perfect for graphic-intensive applications such as 2D/3D rendering video encoding. Able to delivery high-resolution outputs and shorten processing time for designers.
Deep Learning
Effective in reducing machine learning training time from days to minutes. It enables researchers and developers to obtain faster, more accurate information from deep learning
Parallel Processing
By leveraging GPU-powered parallel processing capability, the resource-heavy tasks can be run efficiently at rates up to ten times faster than a counterpart CPU.
Incredible performance in lastest eSport, VR or AAA title. Specialized in rendering and streaming compute-intensive games to deliver the best-quality and smoothest gaming experience to gamers.
Dedicated GPU

High Performance Cloud Server Accelerators for Parallel Computing

With 100% dedicated vCPUs and NVMe SSD storage, Compute Optimized cloud sever plans are most appropriate for workloads that rely heavily on computing power and multitasking, but are less demanding in terms of memory. Compute Optimized plans are perfect solution when it comes to AI, machine learning, and other applications that can benefit from fast, coherent performance and low latency.

Let your cloud server harness the full power of dedicated GPU to achieve ultra-high-performing parallel data computation, machine learning and graphics-intensive projects.

FireBird GPU

Dedicated cloud and dedicated hardware created to produce results at the forefront of AI and deep learning. A high-performance and cost-effective computing resource service. Powered by dedicated physical resources that are not shared with others. Server hosted in Japan

Technology Partners

Product FAQs

GPU servers, as the name suggests, are servers packed with graphics cards, designed to harness this raw processing power. Using an offloading process, the CPU can hand specific tasks to the GPUs, increasing performance.
The main difference between CPU and GPU architecture is that a CPU is designed to handle a wide-range of tasks quickly (as measured by CPU clock speed), but are limited in the concurrency of tasks that can be running. A GPU is designed to quickly render high-resolution images and video concurrently.
Are you considering a new dedicated server? If you’re like most business leaders, graphics processing units, or GPUs, may not be the first hardware add-ons that spring to mind, but they’re definitely worth your attention.
If your application requires serious GPU performance, we can deliver 2, or 4 GPUs peered together into a single root complex using today’s most advanced binding technology. Our FireBird servers are data center grade and equipped with NVIDIA GPU accelerators.
Our team has experience with Masternodes and would be available to help engineer the best solution for your application.
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