Powered by Advanced GPUs
Our cheap GPU dedicated server offers the computational foundation required to bring innovations to life, like training an AI model, rendering stunning videos, conducting scientific research, accelerating data analysis tasks, and so much more.
Effortlessly host compute-heavy tasks with exceptional speed offered by NVIDIA GPU and top-quality hardware with guaranteed dedicated resources.
Browse and choose from available options like NVIDIA A5000, A6000, A40, and A100. Each GPU is tailored to offer exceptional speed, efficiency, precision, and power.
Each dedicated server with GPU is powered by AMD EPYC and Intel Xeon processors, paired with high-speed DDR4 RAM and NVMe SSDs, for optimal performance.
Our cheap GPU dedicated servers at Tier IV Mumbai data center guarantee 99.95% uptime, minimal latency, and maximum efficiency.
We, at host.co.in, are focused on delivering the best GPU server hosting. To make things better for you, our team of GPU server specialists is available 24/7 to help you.
The easily Customisable GPU dedicated server solutions allow you to effortlessly upgrade your configurations to meet growing business needs without any interruption.
Make use of the extremely fast processing power offered by our dedicated server with GPU. It accelerates demanding work like 3D rendering, AI model training, and other computational workloads.
Secure your data, intensive workloads, and applications with our enterprise-grade security, available round the clock on a standalone dedicated server environment.
You’ll receive 24/7 expert support anywhere and at any time with our GPU server hosting, so your website functions uninterruptedly.
Parallel
processing
Effective resource consumption
Stream processing
Scalable & flexible resources
Improved
performance
Easy
compatibility
Enterprise-level GPU dedicated server hardware for excellent performance.
Ensure outstanding performance since there’s no resource sharing.
Easily scale server configurations whenever your demands increase.
Relax and let our managed support team handle the server and security.
Complies with the industry standard protocols for data safety.
Offers greater computing power at a lower cost.
| GPU | RTX A5000 | RTX A6000 | L4 | L40S | A100 PCIe |
|---|---|---|---|---|---|
| Architecture | Ampere | Ampere | Ada Lovelace | Ada Lovelace | Ampere |
| CUDA Cores | 8192 | 10752 | 7424 | 18176 | 8192 |
| Tensor Cores | 256 | 336 | 240 | 568 | 432 |
| Memory (Type) | 24 GB GDDR6 | 48 GB GDDR6 | 24 GB GDDR6 | 48 GB GDDR6 | 80 GB HBM2e |
| Memory Speed | 768 GB/s | 768 GB/s | 300 GB/s | 864 GB/s | 2000 GB/s |
| Performance (FP32) | 27.8 TFLOPS | 38.7 TFLOPS | 30.3 TFLOPS | 91.6 TFLOPS | 19.5 TFLOPS |
| Memory (Type) | 24 GB GDDR6 | 48 GB GDDR6 | 24 GB GDDR6 | 48 GB GDDR6 | 80 GB HBM2e |
| Bandwidth | 768 GB/s | 768 GB/s | 300 GB/s | 864 GB/s | 2,000 GB/s |
| Best for | Basic Graphics, 3D design, rendering, video editing | Advanced Graphics, 3D design, rendering, video editing, faster, higher performance and more memory than A5000 | Basic video analytics, AI inference, VDI, media streaming | Advanced Data center workloads, video analytics, AI training, inference, VDI, media workloads and streaming | Large Scale AI training, inference, HPC, scientific simulations |
| Performance | Medium | High | Medium | High | Very High |
GPU servers are basically advanced types of servers that make use of Graphics Processing Units (GPUs) along with standard Central Processing Units (CPUs).
Normal CPUs are generally used for processing regular data, whereas GPU servers can manage several tasks simultaneously because they use parallel processing. These servers divide complicated tasks into smaller tasks and process them at the same time.
Hence, GPU servers are mostly useful for video rendering, AI model training, deep learning, scientific simulations, Virtual Desktop Infrastructure (VDI), and other sectors that need high-speed computing power.
A GPU dedicated server or a dedicated server with GPU is mainly a kind of physical bare metal dedicated server machine that comes with one or more high performance Graphics Processing Units (GPUs), in addition to standard Central Processing Units (CPUs). This GPU card is responsible for offering a faster, flexible, and highly stable computing environment.
To put it simply, GPU-enabled dedicated servers put less pressure on the power supplies because they complete demanding tasks using parallel processing and with less energy consumption.
We, at host.co.in, provide powerful and best-in-class cheap GPU dedicated servers powered by NVIDIA A5000, NVIDIA A6000, NVIDIA A40, and NVIDIA A100. These GPU servers are best for running compute-intensive applications such as AI, ML, deep learning, etc.
Moreover, our cheap GPU dedicated servers are located at the Tier IV Mumbai data center, guaranteeing 99.95% uptime, minimal latency, and maximum efficiency for your heavy workloads.
We offer AMD EPYC 7313, 2 x AMD EPYC 7313, and 2 x Intel Gold 6326 processors with our advanced GPU dedicated servers. The Intel Gold processors offer significant performance benefits for resource-heavy applications, and the AMD EPYC processors with higher cores are perfect for extremely parallel applications.
Yes. Select a cheap dedicated server with GPU as per your preference, and for memory, processing power, storage, we provide various options to meet your needs. Get in touch with our sales team to help you design your choice of GPU server configuration.
The Linux dedicated servers with GPUs are highly advantageous for demanding tasks needing high computational power mainly in parallel processing.
Its main benefits include:
1. Improved performance
2. Cost efficiency
3. Scalability
4. Faster processing for AI, ML, HPC, etc.
5. Increase in graphics performance
CUDA cores are basically the core processing units inside NVIDIA GPUs, and they are mainly designed for parallel processing.
Tensor cores are specially tailored processing units within NVIDIA GPUs that help in speeding up heavy workloads related to deep learning and machine learning.
GPU architecture refers to the design and structure of the Graphics Processing Unit (GPU), which shows how the GPU runs and executes different types of computational tasks.