A compute-aware simulation architecture designed to align execution behavior with system structure—prioritizing stability, scalability, and predictability over raw hardware dependence.
In complex simulation environments, computational outcomes are shaped as much by system architecture as by available hardware. Endeavor’s approach treats compute as a structural consideration—integrated into the simulation architecture—rather than an external resource to be maximized.
The goal is not to extract more performance from hardware, but to ensure that execution behavior remains coherent, deterministic, and scalable as system demands increase.
The simulation platform is architected with an awareness of how computation is allocated, scheduled, and sustained during runtime execution. This allows the system to manage workload distribution without fragmenting execution logic or compromising system state.
Key architectural considerations include:
Compute is treated as a constraint to be respected, not a variable to be exploited.
Rather than relying on post-hoc optimization or hardware-specific tuning, efficiency is achieved through architectural coherence. By structuring simulation execution around persistent state and controlled concurrency, the platform avoids unnecessary recalculation, duplication, or execution resets.
This approach emphasizes:
Efficiency emerges from design, not from incremental tuning.
As simulation scope increases—through additional scenarios, concurrent contexts, or extended execution—the architecture maintains a single, coherent execution model. Scaling occurs within the system’s structure rather than through ad hoc extensions or external orchestration layers.
This allows the platform to grow in capability without introducing divergent execution paths or inconsistent system behavior.
The compute architecture is designed to operate independently of deployment model. Whether simulations are executed locally, within controlled environments, or accessed through streamed interfaces, execution behavior remains consistent.
This separation ensures that:
The system adapts to compute environments without being defined by them.
These architectural decisions are part of the platform’s broader system design, independent of specific simulation domains or deployment models.
The compute architecture is deliberately not designed around:
These exclusions are intentional, preserving architectural stability over short-term gains.
Training, operations, or simulation architecture—start with a focused discussion on requirements and deployment context.