Arjun Mehta
Machine Learning Engineer, AI Research Firm
We moved to a GPU dedicated server when training times on CPUs started affecting our research timelines. With dedicated GPU resources, training large models became far more predictable.
⚙ GPU Dedicated Servers
GPU Dedicated Server Power for Workloads That Push Limits
When CPUs Aren't Enough, GPU Dedicated Servers are ones that you Should Use
Run compute-heavy workloads without bottlenecks. ICSDC GPU Dedicated Servers are built for tasks that demand parallel processing, high memory throughput, and consistent performance - ideal for AI training, rendering, simulations, and data-intensive workloads.
⚙ Bare-Metal GPU
99.9% Uptime
Dedicated Resources
Dedicated GPU Compute Power
Access full GPU resources exclusively allocated to your workloads, ensuring consistent performance without shared limitations.
High Memory & Fast Data Throughput
Handle large datasets and parallel tasks efficiently with high-bandwidth memory and optimized data transfer.
Optimized for AI, ML & Rendering
Designed to support training models, running simulations, video rendering, and other compute-intensive tasks smoothly.
Full Control & Custom Environments
Install your preferred OS, drivers, frameworks, and libraries to build a setup tailored to your exact workload needs.
Choose the Right GPU Server Plan
Simple pricing based on GPU type, resources, and performance level - no hidden complexity.
Entry GPU
₹5,999 //mo
Single GPU for inference, development, and smaller workloads
- 1x NVIDIA A100
- 40 GB HBM2e Memory
- 16 Core CPU
- 64 GB ECC RAM
- 960 GB NVMe SSD
- 10 TB Bandwidth
Most Popular
Performance GPU
₹12,999 //mo
High-throughput GPU for AI training and rendering
- 1x NVIDIA H100
- 80 GB HBM3 Memory
- 32 Core CPU
- 128 GB ECC RAM
- 1.92 TB NVMe SSD
- 20 TB Bandwidth
- Priority Support
Enterprise GPU
₹29,999 //mo
Multi-GPU cluster for large-scale AI and HPC
- 4x NVIDIA A100
- 160 GB HBM2e Memory
- 64 Core CPU
- 256 GB ECC RAM
- 3.84 TB NVMe SSD
- Unlimited Bandwidth
- Dedicated Account Manager
The Technology Behind High-Intensity Workloads
Every ICSDC GPU Dedicated Server is built from the ground up for sustained, compute-heavy operations.
True Bare-Metal GPU Performance
ICSDC GPU Dedicated Servers run on physical hardware with no virtualization layers. Your workloads get uninterrupted access to GPU resources with zero performance loss from shared environments.
Enterprise-Class NVIDIA GPU Options
Choose from modern NVIDIA GPUs designed for AI training, machine learning, rendering, and high-performance computing. Built for stability and compatibility with GPU-accelerated frameworks.
Full Root-Level Server Control
Get complete root access to configure your operating system, install drivers, manage GPU settings, and optimize performance based on your exact workload requirements.
High-Speed Network Connectivity
GPU servers are backed by high-bandwidth uplinks designed for low latency data transfer, remote access, distributed processing, and real-time workloads.
Multi-GPU Configurations Available
Scale computes power horizontally with multi-GPU server options. Ideal for parallel processing, advanced model training, rendering pipelines, and simulation workloads.
Global Deployment Options
Deploy GPU servers in strategically located data centers to reduce latency, meet compliance needs, and support geographically distributed teams or applications.
ECC Memory for Compute Stability
Servers are paired with enterprise-grade ECC memory to ensure data integrity, reduce errors, and maintain stability during long-running, compute-intensive tasks.
Optimized Thermal & Power Design
Hardware is configured with advanced cooling and power management to maintain consistent GPU performance during sustained high-load operations.
GPU Compatibility With Containers & Virtualization
Support for GPU passthrough enables usage with container platforms and virtualization tools while retaining direct access to hardware resources.
Ready-to-Use GPU Software Stack
Optional pre-installed NVIDIA drivers and CUDA libraries allow you to start working immediately with popular frameworks like TensorFlow and PyTorch.
Flexible Billing & Configuration Options
Choose configurations and billing plans that align with your workload duration, performance needs, and budget - without long-term rigidity.
Secure & Isolated Infrastructure
Hosted in secure data centers with network protection, private networking options, and controlled access to keep your workloads isolated and protected.
Real-World Applications of ICSDC GPU Dedicated Servers
From AI model training to medical imaging — GPU Dedicated Servers power the workloads that matter most.
AI & Language Models
ICSDC GPU servers are well suited for training and running large language models and NLP workloads. GPU acceleration speeds up model training, embeddings, and inference, making them ideal for chat systems, translation tools, content moderation, and text a
3D Rendering & Visual Workloads
Reduce rendering times for complex scenes using GPU-accelerated rendering engines. Dedicated GPU memory supports high-resolution textures, lighting calculations, and real-time previews - useful for design studios, architects, and animation teams.
Autonomous Systems & Simulation
GPU-powered servers handle large datasets used in simulations, sensor data processing, and decision-making models. Multi-GPU configurations support parallel workloads for research, testing, and development of autonomous and robotics systems.
Blockchain & Distributed Compute
Run GPU-intensive blockchain workloads such as cryptographic processing, smart contract execution, and validation tasks. Dedicated GPU resources ensure predictable performance for decentralised and compute-driven blockchain environments.
AI Inference & Model Serving
Deploy trained models for real-time inference at scale. ICSDC GPU servers provide consistent performance for image recognition, speech processing, recommendation systems, and other inference-heavy applications used in production environments.
Medical Imaging & Data Analysis
Process large imaging datasets such as CT scans, MRI images, and diagnostic visuals using GPU-accelerated models. High memory capacity and stable compute performance support healthcare analytics, research, and diagnostic tooling.
Virtual Reality & Simulation Environments
Power immersive VR applications with low latency and high frame rates. Dedicated GPUs handle real-time rendering, physics calculations, and interactive simulations for training, education, and enterprise use cases.
Game Development & Build Pipelines
Support game engines and development workflows with GPU-accelerated builds, asset processing, and real-time testing. Suitable for studios working on high-quality visuals, physics simulations, and performance-critical game components.
Financial Analytics & Fraud Detection
Run GPU-accelerated models that analyse large transaction datasets in near real time. High parallel processing capability helps identify anomalies and patterns for fraud detection, risk analysis, and financial modelling.
Ready to see if a GPU Dedicated Server fits your workload?
Talk to our GPU infrastructure experts and find the right configuration for your AI, rendering, or HPC needs.
Compare GPU Capabilities Across Workloads
| GPU Model | Memory / Type | Bandwidth (GB/s) | Power (W) | FP64 (TFLOPS) | FP32 (TFLOPS) | INT8 (TOPS) | Suggested Use Cases |
|---|---|---|---|---|---|---|---|
| NVIDIA L40S | 48 GB GDDR6 | ~864 | ~350 | N/A | ~91.6 | 733 | Inference, graphics, mixed AI/visual workloads |
| NVIDIA H100 | 80 GB HBM3 | ~3350 | ~700 | N/A | ~60 | 1216 | Large AI training, HPC & deep learning |
| NVIDIA Tesla T4 | 16 GB GDDR6 | ~300 | ~70 | N/A | ~8.1 | 130 | Edge inference, video transcoding |
| NVIDIA L4 | 24 GB GDDR6 | ~300 | ~72 | N/A | ~30 | 147 | AI inference, video/vision workloads |
| NVIDIA H200 | 141 GB HBM3e | ~4800 | ~700 | N/A | N/A | N/A | Next-generation AI training & HPC |
| NVIDIA A30 | 24 GB HBM2 | ~933 | ~165 | N/A | ~10.3 | 330 | AI training, general HPC tasks |
| AMD MI210 | 64 GB HBM2e | ~1600 | ~300 | ~11.9 | ~22.7 | N/A | FP64-heavy HPC, large compute jobs |
| NVIDIA A100 | 40 GB HBM2e | ~1555 | ~250-300 | ~9.7 | ~19.5 | 624 | AI training, analytics |
| NVIDIA RTX A4000 | 16 GB GDDR6 ECC | ~448 | ~140 | N/A | ~19.2 | N/A | Graphics & mid-range compute |
| NVIDIA RTX A5000 | 24 GB GDDR6 ECC | ~768 | ~230 | N/A | ~27.8 | ~444 | High-end graphics, AI & compute |
Why Choose ICSDC GPU Dedicated Servers?
ICSDC GPU Dedicated Servers are built for organisations that need dependable performance, consistent availability, and infrastructure that can handle sustained, compute-heavy workloads without compromise.
Reliable 99.9% Uptime Commitment
Our GPU servers are hosted on robust infrastructure designed for high availability. Redundant power, network connectivity, and continuous monitoring help ensure your workloads remain accessible and operational.
Built for Long-Running, High-Load Tasks
ICSDC GPU servers are designed to handle intensive workloads such as AI training, data processing, rendering, and simulations. They maintain stability even during prolonged, resource-heavy operations.
Enterprise-Grade Data Center Environment
Your servers are hosted in secure, professionally managed data centers with controlled access, power backups, and network redundancy to support critical workloads.
Balanced Performance Across Compute, Memory & Storage
Our GPU servers are configured to maintain an effective balance between GPU power, CPU capability, memory, and fast storage - ensuring no single component becomes a bottleneck.
Consistent Performance Without Resource Sharing
Dedicated hardware means your GPU, memory, and compute resources are not shared with other users. This results in predictable performance and better workload isolation.
Suitable for a Wide Range of GPU Workloads
From AI and machine learning to rendering, analytics, and simulation tasks, ICSDC GPU servers support diverse use cases without requiring infrastructure changes.
Designed for Practical Long-Term Value
GPU servers represent a higher-performance alternative to CPU-only systems. For workloads that benefit from parallel processing, they offer better efficiency and scalability over time.
Scalable Infrastructure as Requirements Grow
As workloads evolve, ICSDC's infrastructure allows for configuration flexibility, helping teams adapt without rebuilding their environments from scratch.
NVIDIA GPU Options Available with ICSDC Dedicated Servers
From LLM training to VDI — we have the right GPU for every high-compute workload.
NVIDIA GH200 Grace Hopper Superchip
Integrated CPU - GPU architecture with shared high-bandwidth memory, designed for large-scale AI training and HPC workloads requiring low-latency data movement.
NVIDIA HGX H100 Tensor Core GPU
Hopper-based GPU optimized for large language models, deep learning training, and high-throughput parallel compute with advanced tensor core support.
NVIDIA A100 Tensor Core GPU
Multi-purpose GPU for AI training, inference, and analytics, supporting multi-instance GPU (MIG) for workload isolation and resource partitioning.
NVIDIA L40S GPU
Data-center GPU combining AI inference and graphics acceleration, suitable for mixed workloads including rendering and visual compute.
NVIDIA A40 GPU
Professional GPU focused on visual computing, ray tracing, and simulation with support for graphics and AI-assisted workflows.
NVIDIA A16 GPU
VDI-focused GPU designed for high-density virtual desktops with efficient GPU sharing and consistent user performance.
When Should You Choose a GPU Dedicated Server?
- AI and machine learning workloads that require parallel processing
- Large datasets that need faster compute and memory bandwidth
- Applications limited by CPU-only performance
- Rendering, simulation, or visual compute tasks
- Workloads needing isolated, dedicated GPU resources
- Low-latency processing and high-throughput compute
- Full control over GPU drivers, frameworks, and OS
Read ICSDC GPU Dedicated Server Client Stories
FAQs about ICSDC GPU Dedicated Server
01What is a GPU Dedicated Server used for?
A GPU Dedicated Server is used for workloads that benefit from parallel processing, such as AI training, machine learning, rendering, simulations, and large-scale data processing.
02How is a GPU Dedicated Server different from a CPU server?
GPU servers are designed to handle many computations simultaneously, while CPU servers handle tasks sequentially. This makes GPUs much faster for AI, graphics, and compute-heavy workloads.
03Do I get full control over the GPU server?
Yes. You get full root access, allowing you to install your preferred operating system, GPU drivers, libraries, and frameworks based on your workload requirements.
04Can I use the GPU server for both training and inference?
Yes. GPU Dedicated Servers can be used for model training, fine-tuning, inference, rendering, and other GPU-accelerated tasks depending on the configuration you choose.
05Are GPU resources shared with other users?
No. The GPU, CPU, memory, and storage resources are fully dedicated to your server, ensuring consistent and predictable performance.
06What kind of workloads benefit most from GPU servers?
Workloads involving large datasets, image or video processing, deep learning models, scientific simulations, and real-time rendering benefit the most from GPU acceleration.
07Can I scale or upgrade my GPU server later?
Yes. Depending on availability, configurations can be adjusted to support higher GPU capacity, additional resources, or different GPU models as your requirements evolve.
08Is technical expertise required to manage a GPU Dedicated Server?
Basic server management knowledge is recommended. However, ICSDC provides support to help with setup guidance, access issues, and general configuration questions.
Take the next step toward faster, more reliable compute performance.
Bare-metal NVIDIA GPU servers from ₹14,999/month. Full root access, ECC memory, no virtualization.