High-Performance Computing (HPC) services help organizations design, build, and operate advanced compute environments for AI/ML, simulation, research, analytics, rendering, and complex engineering workloads. We deliver end-to-end HPC capabilities—from strategy and architecture to cluster deployment and managed operations—ensuring performance, scalability, and efficiency.
Whether you’re building a research cluster, AI training infrastructure, engineering simulation environment, or enterprise HPC platform, Maayan enables high-throughput, low-latency compute at scale.
Modern HPC environments deliver competitive advantage when aligned to measurable outcomes:
Faster simulation and model training
Reduced time-to-insight for research and analytics
Higher compute efficiency (performance per watt)
Scalable infrastructure for AI and GPU-heavy workloads
Improved workload scheduling and resource utilization
Secure, compliant, and resilient compute environments
We align HPC architecture to measurable goals—faster simulations, shorter AI training cycles, higher throughput, and improved performance-per-watt.
Deep capability in high-density GPU clusters, distributed AI training, and scalable compute fabrics built for modern workloads.
From workload assessment and cluster design to deployment, benchmarking, and managed optimization—one accountable partner.
We optimize compute, storage, and network fabrics while embedding energy efficiency and cost governance (FinOps for HPC).
Low-latency interconnect design ensures efficient distributed computing and parallel processing at scale.
Cluster blueprints that allow phased growth without disrupting running workloads.
Segmentation, privileged access governance, and audit-ready controls embedded into HPC environments.
Benchmarking, capacity planning, and workload tuning frameworks ensure sustained performance gains beyond go-live.
Maayan Technologies delivers end-to-end HPC capabilities—from strategy and architecture to cluster deployment and managed optimization—ensuring scalable, high-throughput, low-latency compute environments built for AI, engineering simulation, analytics, and scientific workloads.
Define the right compute model aligned to performance, scalability, and ROI objectives.
Workload profiling (AI/ML, CFD, FEA, genomics, rendering, analytics)
Compute sizing (CPU/GPU balance, memory, storage, network bandwidth)
Benchmarking strategy and performance modeling
TCO/ROI modeling and phased growth roadmap
Design resilient, scalable clusters optimized for performance and future expansion.
Compute node architecture planning (CPU/GPU density, memory ratios)
High-speed interconnect topology design (InfiniBand/Ethernet patterns)
Parallel file system architecture and performance tuning strategy
High availability (HA), redundancy, and fault tolerance design
Deploy high-density GPU clusters for distributed AI training and inference workloads.
GPU server architecture planning and rack density modeling
Power and cooling readiness assessment for high-density deployments
Multi-node cluster configuration and workload orchestration guidance
Performance tuning for distributed AI frameworks
Build high-throughput, low-latency storage environments for demanding workloads.
Tiered storage architecture (NVMe, SSD, archival tiers)
Parallel file system planning and optimization
High-speed data ingestion and movement patterns
Backup, disaster recovery, and data lifecycle governance
Deliver low-latency, high-bandwidth connectivity for compute-intensive environments.
Leaf-spine and high-speed fabric design
Latency, throughput, and congestion optimization
Secure cluster segmentation and access governance
Network monitoring and performance validation frameworks
Enable efficient workload scheduling and resource management across clusters.
Job scheduler configuration and governance
Containerized workload enablement and orchestration patterns
Library/toolchain alignment for AI and scientific computing
Utilization dashboards and performance analytics reporting
Align HPC clusters with facility readiness and energy efficiency goals.
Rack layout and white-space optimization
Power distribution and redundancy architecture planning
Cooling containment and airflow optimization
Performance-per-watt KPI tracking and cost optimization routines
Operate, monitor, and continuously optimize HPC environments for reliability and efficiency.
Monitoring, incident management, and change governance
Capacity planning and utilization optimization
Performance tuning and scaling strategy refinement
Quarterly value reviews and continuous improvement roadmap
As computational demands surge with AI, simulation, and advanced analytics workloads, organizations need comprehensive, industry-tailored High-Performance Computing (HPC) solutions to compete in the next generation of innovation.
Maayan Technologies combines deep engineering expertise, scalable architecture design, and cross-industry insight to build and optimize high-performance compute environments. Our global experience ensures clients are prepared to address evolving performance, scalability, efficiency, and research challenges in an increasingly compute-intensive world.
Maayan Technologies provides structured accelerators that reduce deployment risk, optimize performance, and ensure long-term scalability for HPC and AI-intensive workloads.
HPC reference architectures (CPU/GPU clusters, AI training patterns)
Capacity and performance modeling toolkits
Rack density and GPU-ready data center blueprint
Cluster commissioning and benchmarking templates
Scheduler governance and workload prioritization frameworks
Energy efficiency and performance-per-watt optimization checklist
Security-by-design patterns (segmentation, access, audit logs)
Pilot-to-scale rollout playbook for research and enterprise HPC
At Maayan Tech, we are committed to providing exceptional service and support. Your questions, feedback, and inquiries are important to us, and we will do our best to respond promptly. Whether you’re a business seeking technology solutions or an individual with a query, we are here to assist you.