Do you offer custom GPU clusters with H100 A100 and H200?

Yes, Cyfuture Cloud offers fully customizable GPU clusters featuring NVIDIA H100, A100, and H200 GPUs. These high-performance configurations support AI, machine learning, HPC workloads, and more, with flexible scaling, rapid provisioning, and enterprise-grade support tailored to your needs.

Cyfuture Cloud stands at the forefront of GPU-accelerated cloud computing, delivering bespoke infrastructure for demanding computational tasks. As a leading Indian cloud provider based in Delhi, we specialize in NVIDIA's latest GPU architectures, including the powerhouse H100, versatile A100, and next-gen H200. Our custom GPU clusters empower businesses, researchers, and developers to build scalable, high-throughput environments without the overhead of on-premises hardware.

Understanding Custom GPU Clusters

Custom GPU clusters at Cyfuture Cloud go beyond off-the-shelf instances. You specify the GPU type (H100 for maximum FP8/FP16 performance, A100 for balanced multi-precision workloads, or H200 for enhanced memory bandwidth up to 4.8 TB/s), cluster size (from single nodes to hundreds of GPUs), interconnects (like NVIDIA NVLink or InfiniBand for low-latency multi-GPU communication), storage (NVMe SSDs or high-IOPS cloud volumes), and networking (up to 400 Gbps RDMA).

Provisioning happens in minutes via our intuitive dashboard or API. For example, a typical AI training cluster might include 8x H100 SXM GPUs per node, interconnected via NVSwitch, with 2 TB RAM and 100 Gbps Ethernet uplinks. We handle everything from bare-metal deployment to optimized software stacks like CUDA 12.x, cuDNN, and frameworks such as TensorFlow, PyTorch, or RAPIDS.

Key Benefits:

- Scalability: Auto-scale clusters dynamically based on workload demands, bursting to thousands of GPUs.

- Cost Efficiency: Pay-as-you-go or reserved instances, up to 40% cheaper than hyperscalers for sustained workloads.

- Performance: H100 delivers 4x faster inference than A100; H200 adds 1.4x memory capacity for larger models like LLMs.

- India-Centric: Low-latency access from Delhi data centers, compliant with DPDP Act and MeitY guidelines.

GPU Specifications and Use Cases

Here's a quick comparison of supported GPUs:

Real-World Examples:

- AI/ML Training: A fintech client deployed a 64x H100 cluster to train fraud detection models 3x faster.

- HPC Simulations: Researchers used A100 clusters for climate modeling, processing petabytes of data.

- Rendering/VFX: Media firms leverage H200 GPU for real-time ray tracing in film production.

We integrate with Kubernetes (via NVIDIA GPU Operator), Slurm for job scheduling, and tools like Weights & Biases for experiment tracking. Security features include VPC isolation, encrypted data at rest/transit, and SOC 2 compliance.

Deployment and Management

Getting started is straightforward:

1. Configure: Use our GPU Cluster Builder tool to select GPUs, node count, and OS (Ubuntu, CentOS, or custom images).

2. Deploy: One-click launch with pre-tuned kernels for optimal throughput.

3. Monitor: Real-time metrics via Prometheus/Grafana dashboards; auto-alerts for utilization spikes.

4. Optimize: Expert support for MIG partitioning (e.g., slice H100 into 7 instances) or multi-node scaling.

Our Delhi-based data centers ensure <10ms latency for Indian users, with global peering. SLAs guarantee 99.99% uptime, and we offer white-glove onboarding for clusters >50 GPUs.

Pricing and Support

Pricing starts at ₹150/GPU-hour for A100, ₹250 for H100, and ₹300 for H200 (volume discounts apply). No egress fees within India. Enterprise plans include 24/7 support, custom SLIs, and dedicated cluster managers.

Backed by Cyfuture's 10+ years in cloud infra, we serve 5000+ customers across BFSI, healthcare, and edtech.

Conclusion

Cyfuture Cloud's custom GPU clusters with H100, A100, and H200 deliver unmatched performance, flexibility, and value for your compute-intensive needs. Whether training massive models or running complex simulations, our tailored solutions accelerate innovation while minimizing costs. Contact 

[email protected]  to design your cluster today.

Follow-Up Questions

Q: How quickly can I provision a custom H100 cluster?
A: Clusters are provisioned in under 15 minutes for standard configs; complex setups (100+ GPUs) take 1-2 hours with engineer assistance.

Q: Do you support hybrid CPU-GPU clusters?
A: Yes, pair GPUs with AMD EPYC or Intel Xeon CPUs, scalable to 10,000+ cores per cluster.

Q: What software stacks are pre-installed?
A: NVIDIA NGC containers, Docker, Kubernetes, plus ML frameworks. Custom images supported via our marketplace.

Q: Are there minimum commitments?
A: No minimums for on-demand; reserved contracts start at 1 month for discounts up to 50%.

Q: How does latency compare to AWS/GCP in India?
A: Our Delhi edge reduces latency by 30-50% for local workloads, with direct peering to major ISPs.