Massively Parallel Backtesting Grid
Run thousands of parameter sweeps using tokenized GPU units with configurable compute spend.
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Capability pillar
Tokenized GPU pools for sweeps, evolution, and RL—with spend controls and reproducible manifests.
Parameter grids burn compute tokens deliberately; manifests bind code, data slices, and kernels so results replay bit-for-bit.
Run thousands of parameter sweeps using tokenized GPU units with configurable compute spend.
Evolve strategies via mutation, crossover, and multi-objective fitness using compute credits.
Train RL agents (PPO, DQN, SAC) on synthetic or historical order books with custom reward functions.
Model realistic microstructure: slippage, queue position, routing delays, and venue-specific latency.
GPU-accelerated correlation matrices, PCA, clustering, and anomaly detection with interactive exploration.