Rise VAST (Virtualized AI Computing Scalability Technology), co-developed by RiseUnion and 4Paradigm as "HAMi Enterprise Edition", delivers enterprise-grade resource orchestration through software-defined heterogeneous compute pooling. The platform enables advanced GPU virtualization, fractional allocation, and intelligent priority management, driving superior resource efficiency while reducing AI infrastructure TCO. Rise VAST powers the infrastructure foundation for Rise CAMP orchestration and provides robust compute management for Rise MAX appliances.
Built upon the proven HAMi Open Source Foundation, Rise VAST introduces comprehensive enterprise capabilities including GPU memory oversubscription, resource preemption and expansion, custom compute profiles, NVLink topology optimization, policy-driven scheduling, enterprise-grade isolation, quota enforcement, multi-cluster federation, audit logging, high availability, and comprehensive operational analytics. As the foundational infrastructure for the RiseUnion ecosystem, VAST provides robust platform support for Rise CAMP orchestration and Rise MAX deployment solutions.
RiseUnion and 4Paradigm have established a strategic partnership to deliver enterprise-class AI resource pooling: Rise VAST (HAMi Enterprise Edition). This collaboration accelerates innovation in AI resource management and model optimization workflows. By combining HAMi's advanced scheduling capabilities with 4Paradigm's AI platform expertise, we provide comprehensive AI infrastructure solutions for enterprise customers.
Advanced GPU partitioning with fractional allocation, memory oversubscription, and isolation guarantees. Optimized for small model workloads with fine-grained resource sharing and multi-tenant efficiency.
Unified GPU resource pooling with topology-aware scheduling, workload placement optimization, and dynamic rebalancing across heterogeneous accelerator environments.
Intelligent memory oversubscription with QoS guarantees, enabling allocation of virtual GPU memory beyond physical limits while maintaining performance isolation and workload SLAs.
Purpose-built optimizations for small language models including batch optimization, GPU multiplexing, and inference-specific scheduling policies to maximize throughput and resource efficiency.
Automated GPU partitioning with dynamic MIG instance management, enabling flexible resource allocation and optimal utilization for diverse workload requirements.
Comprehensive monitoring, alerting, and centralized management console with real-time resource visibility, performance analytics, and automated operational workflows.
Expert engineering support with deep platform knowledge and AI infrastructure expertise, ensuring optimal resource utilization and maximum return on AI infrastructure investments.
Enterprise SLA with 24/7 monitoring, proactive support, and guaranteed response times to ensure continuous availability and performance for business-critical AI workloads.
Expert consultation on GPU pool architecture, resource allocation strategies, and performance tuning to optimize infrastructure efficiency and cost effectiveness.
Regular platform updates with new scheduling algorithms, performance optimizations, security enhancements, and feature additions delivered through managed release cycles.
Comprehensive training and certification programs for platform administrators, ML engineers, and operations teams to maximize platform capabilities and operational efficiency.
Pre-validated integrations with leading MLOps toolchains, container platforms, and cloud services, enabling seamless workflow integration and vendor interoperability.
