Hardware Sizing
How many GPUs per slot, slots per chassis, and chassis per rack? VisualSim provides what-if analysis to prevent overdesign or underprovisioning.
Software Partitioning
Partition workloads (LLMs, inference, analytics, video, telecom) across GPUs, CPUs, and memory. Measure end-to-end task latency from prompt to response.
Data Center Efficiency
Generate utilization heatmaps for GPUs, interconnects, and memory to ensure sustained 75–80% utilization.
Operating Cost / Electricity
Model rack-level power consumption, cooling overhead, and cost per task. Identify efficiency gains that translate into millions saved annually.
Bottleneck Identification
Measure latency across NVLink, NVSwitch, NVFusion, Ethernet, and memory hierarchies. Locate stalls in interconnects, queues, or memory maps.
System Planning
Conduct trade-off studies for different interconnect topologies, memory maps, and redundancy policies. Ensure scalability from edge devices to hyperscale data centers.
Beyond Training and Inference
VisualSim applies equally to HPC, analytics, 5G/6G telecom, simulation, aerospace/defense, and video processing — anywhere GPU-based architectures dominate.
GPUs, CPUs, accelerators, caches, DRAM/HBM, interconnects, SSDs, power supplies.
Import real workloads or traces to simulate LLMs, inference, video streams, or telecom traffic.
Latency, throughput, concurrency scaling.
Electricity cost per rack and per transaction.
Failover, redundancy, and recovery impacts.
Map technical results directly into CapEx avoidance, OpEx reduction, and faster payback.
CapEx Optimization
Avoid overbuying GPUs → \$125M saved.
OpEx Savings
Reduce electricity and cooling → \$5M+ saved annually per facility
Revenue Growth
Faster response → 12% more billable transactions per rack
Risk Mitigation
Prevent downtime penalties and contract failures.
Payback Acceleration
From 5+ years to \~3 years with VisualSim-optimized architectures.
Hyperscale Cloud Provider
Telecom Edge AI
Automotive Edge Computing
Defense & Aerospace
