We provide high-speed implementations for simulating reservoirs described by $N$-coupled spin-torque oscillators. Here $N$ also corresponds to the number of reservoir nodes. We benchmark a variety of implementations based on CPU and GPU. Our new methods are at least 2.6 times quicker than the baseline for $N$ in range $1$ to $10^4$. More specifically, over all implementations the best factor is 78.9 for $N=1$ which decreases to 2.6 for $N=10^3$ and finally increases to 23.8 for $N=10^4$. GPU outperforms CPU significantly at $N=2500$. Our results show that GPU implementations should be tested for reservoir simulations. The implementations considered here can be used for any reservoir with evolution that can be approximated using an explicit method.

翻译：我们提供了描述由$N$个耦合自旋扭矩振荡器构成的储层的高效仿真实现方案，其中$N$同时对应储层节点数。我们基于CPU和GPU对多种实现方案进行了基准测试。当$N$在1到$10^4$范围内时，新方法比基线方法快至少2.6倍。具体而言，在所有实现方案中，最佳加速比在$N=1$时为78.9倍，当$N=10^3$时降至2.6倍，最终在$N=10^4$时升至23.8倍。当$N=2500$时，GPU性能显著优于CPU。我们的结果表明，应该针对储层仿真测试GPU实现方案。本文考虑的实现方案可适用于任何演化过程可通过显式方法近似的储层系统。