Gpu Infrastructure

No Idle GPUs, No Data Leakage: QumulusAI Maximizes GPU Utilization for Multiple Customers on Shared Infrastructure

Multi-tenant GPU infrastructure is becoming essential as AI deployments scale across customers. Organizations must maximize GPU utilization while maintaining strict data isolation. Idle compute reduces efficiency, yet shared environments can introduce security risks if not designed properly. Optimizing GPU cycles across multiple customers is essential to maintaining performance and cost efficiency. Mazda Marvasti, the…

Amberd Moves to the Front of the Line With QumulusAI’s GPU Infrastructure

Reliable GPU infrastructure determines how quickly AI companies can execute. Teams developing private LLM platforms depend on consistent high-performance compute. Shared cloud environments often create delays when demand exceeds available capacity. Amberd CEO Mazda Marvasti says waiting for GPU capacity did not align with his company’s pace. Amberd required guaranteed availability to support its…

QumulusAI Secures Priority GPU Infrastructure Amid AWS Capacity Constraints on Private LLM Development

Developing a private large language model (LLM) on AWS can expose infrastructure constraints, particularly around GPU access. For smaller companies, securing consistent access to high-performance computing often proves difficult when competing with larger cloud customers. Mazda Marvasti, CEO of Amberd, encountered these challenges while scaling his company’s AI platform. Because Amberd operates its own…

Facing High GPU Costs and Infrastructure Constraints, Amberd Turned to QumulusAI for Fixed-Cost AI

Providing managed AI services at a predictable, fixed cost can be challenging when hyperscaler pricing models require substantial upfront GPU commitments. Large upfront commitments and limited infrastructure flexibility may prevent providers from aligning costs with their delivery model. Amberd CEO Mazda Marvasti encountered this issue when exploring GPU capacity through Amazon. The minimum requirement…

OpenAI–Cerebras Deal Signals Selective Inference Optimization, Not Replacement of GPUs

OpenAI’s partnership with Cerebras has raised questions about the future of GPUs in inference workloads. Cerebras uses a wafer-scale architecture that places an entire cluster onto a single silicon chip. This design reduces communication overhead and is built to improve latency and throughput for large-scale inference. QumulusAI Senior Product Manager Mark Jackson says Cerebras’…

No Idle GPUs, No Data Leakage: QumulusAI Maximizes GPU Utilization for Multiple Customers on Shared Infrastructure

Multi-tenant GPU infrastructure is becoming essential as AI deployments scale across customers. Organizations must maximize GPU utilization while maintaining strict data isolation. Idle compute reduces efficiency, yet shared environments can introduce security risks if not designed properly. Optimizing GPU cycles across multiple customers is essential to maintaining performance and cost efficiency. Mazda Marvasti, the…

Applied Digital Investor Day Highlights

At Applied Digital’s inaugural Investor Day, speakers from various sectors of the company and its partners shared insights on the company’s strategic advancements and future goals. The event underscored Applied Digital’s role in shaping the trajectory of high-performance computing and AI technologies. Key takeaways included: 1. Expansion of capacity to hundreds of megawatts and securing…