Unlock the Power of AI/ML with Virtual Disaggregation

Enterprise Customers

• DynamicXcelerator enables enterprises to optimize GPU utilization cost-effectively. From financial trading to data science, users can deploy isolated vPODs with guaranteed resources for their AI/ML workloads.

AI as a Service

• DynamicXcelerator allows enterprises and cloud service providers to create tailored vPODs, load AI models, and deliver high-performance resources to internal or external users as if they were personal, bare-metal servers.

Complete GPU Server and Interconnect Integration

• Combine resources into vPODs across servers, photonic fabric, and GPU generations.

Efficient Resource Utilization

• Isolate GPUs for specific workloads. For example, an 8-GPU server can host three vPODs: one with 5 GPUs, one with 2, and another with 1 GPU.

Dedicated Performance

• DynamicXcelerator ensures isolated, high-performance peripherals using industry-standard server technology.

Cost-Effective Flexibility

• Works with standard servers and RDMA-capable NICs, reducing hardware costs while ensuring efficient GPU utilization—even with mixed-generation systems.

One core capability of the DynamicXcelerator is virtual Performance Optimized Datacenters (vPODs), which create dynamic resource grouping across multiple physical compute systems, enabling organizations to overcome the inherent constraints of single-node architectures.

vPODs (virtual Pods) unlock a more flexible, efficient approach to infrastructure by enabling:

• Dynamic Resource Allocation
  Distribute workloads across systems for maximum performance and efficiency.
• Independent, Just-in-Time Scaling
  Add exactly the resources you need, when you need them—no overprovisioning required.
• Extended Hardware Lifecycles
  Maximize the value of expensive components by repurposing them across workloads.
• Custom Configurations
  Deploy pods with domain-specific accelerators and software tailored to your needs.
• Operational Flexibility
  Maintain fault isolation between pods while adopting a pay-as-you-grow model to control costs.
• Boundary-Free Design
  Build logical infrastructure that extends beyond physical server or chassis limitations.

• Dynamic Scalability: Allocate additional GPUs to vPODs based on evolving workloads.
• Maximized GPU Utilization: Optimize every resource for peak performance.
• Affordable AI Deployment: Reduce costs by leveraging off-the-shelf hardware.