AI Infrastructure Bottleneck Allocator

CapEx resource balance simulator for AI infrastructure investors

Real-Time Simulation
Resource Allocation
Config

Tune cluster hardware boundaries to reveal limiting physical factors.

Compute Fleet (H100/B200 Eq.) 1,024 units
Unit cost: $32k/accelerator footprint
Grid Interconnect Power 45.0 MW
Substation capacity delivered to data center floor
Interconnect & Memory Bandwidth 32.0 TB/s
High-bandwidth cross-pod collective exchange rate
Thermal Cooling Capacity 5,000 Tons
Direct-to-chip chilled loop & adiabatic tower capacity
Cluster Resource Topology & Constriction
Optimal
Constrained
Choked
Topology State: Analyzing flow through 4 infrastructure stages... 840.5 TFLOPS Realized
Physics Model: Compute clusters cannot exceed the envelope defined by thermodynamics and Amdahl/Gustafson scaling. Any mismatch between power delivery, liquid heat extraction, or memory bus width strands expensive silicon into zero-return idle cycles.
Efficiency & Bottleneck Audit
Effective Cluster Throughput
840.5 TFLOPS/chip
Realized workload computation vs theoretical max
Capital Efficiency Ratio
0.74 Fair Balance
Realized CapEx value per invested infrastructure dollar
Constrained by Power
Primary Constriction: Power Grid Capacity.

Grid delivery of 45.0 MW caps continuous cluster power. Additional GPUs cannot be driven at peak frequencies without under-volting or stranding nodes.

Power Grid Load 100% (Cap)
Thermal Headroom 78%
Memory Bus Utilization 83%
Silicon CapEx Utilization 74%
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