Industry veteran with over 10 years of experience architecting and managing GPU-powered cloud solutions.
Specializes in enabling scalable AI/ML and HPC workloads for enterprise and research applications.
Former lead solutions architect for top-tier cloud providers and startups in the AI infrastructure space.
Quick Answer For AI inference, choose H100 for production LLMs, H200 for 70B long-context, B200 for frontier scale, A100 or L40S for cost efficiency, L4 for low-power edge, RTX 6000 Ada or RTX 5090 for experimentation, and MI300X/MI325X or Gaudi 3 alternatives. A startup launches its AI assistant on Monday. By Friday, the model is […]
Artificial Intelligence (AI) has become the backbone of enterprise innovation. It powers generative AI applications and accelerates predictive analytics. Yet, behind every successful AI model lies a critical decision: should workloads run on virtualized GPUs (vGPUs) or bare-metal GPU servers? This decision is foundational and consequential. According to an IDC report, enterprise spending on AI […]
PyTorch is an open-source machine learning framework that feels less like a rigid tool and more like a natural extension of Python itself. Developed by Facebook’s AI Research lab (FAIR), its Python-first design and dynamic computation graphs have made it a favorite for researchers and developers who need to prototype quickly and build complex neural […]
Unlock the potential of GPUs in healthcare imaging. Explore how GPU technology is revolutionizing diagnosis for better patient outcomes. Learn more.
Enterprises can use GPU-as-a-Service (GPUaaS) to rent managed GPU compute in the cloud instead of buying and operating hardware. Providers package compute, storage and networking with curated images and orchestration so you can run AI, HPC or 3D workflows quickly. Did you know 40 percent of organizations say they use GPU-as-a-Service (GPUaaS) today, up from 34 percent […]
Running machine learning workloads on CPU-only servers can feel painfully slow, often turning model training into a frustrating experience. Fortunately, by setting up cuDNN for GPU acceleration, you can unlock a significant boost in performance. With the right cuDNN configuration, it delivers substantial speedups vs CPU-only execution, but exact gains depend on model, precision, GPU […]
GPU in medical imaging is moving from a niche tool to a must-have for modern radiology. Medical imaging creates large 3D datasets that can overwhelm traditional computing. This slows down time-to-image and time-to-report. GPUs solve this problem by running imaging tasks in parallel. This method suits voxel-based reconstruction, segmentation, registration and interactive visualization. An ISMRM abstract/report on MRI reconstruction (gGRAPPA) says up to 65× GPU […]
Cloud GPU for AI has become the backbone of modern high-performance computing, especially for training and deploying machine learning models. The combination of GPU acceleration and cloud infrastructure delivers unmatched scale, flexibility and performance for AI and ML workloads. Today, high-performance computing (HPC) combined with GPU acceleration is powering breakthroughs across industries ranging from healthcare […]
You have two great GPUs on the table for AI inference: L40S and A100. The right choice depends on model shape, context length, batch size and isolation needs. Ideally, L40S shines when a single GPU can carry the whole graph with low precision. A100 steps up when memory gets tight or the model spans multiple […]
NVIDIA H100 pricing in India depends on one important question: do you want to buy the GPU outright or rent H100 cloud capacity for AI workloads? In 2026, buying an NVIDIA H100 in India can cost around ₹28 lakh to ₹40 lakh per GPU, depending on the variant, seller, warranty, import route and availability. That […]