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.

我们提供了高速实现方法，用于模拟由N个耦合的自旋转矩振荡器描述的沉积。我们对基于CPU和GPU的各种实现进行了基准测试。我们的新方法在N范围为1到$10^4$时至少比基线快2.6倍。具体而言，在所有实现中，N=1时的最佳因子为78.9，随着N增加到$10^3$，该因子减小到2.6，最后在N=$10^4$时增加到23.8。在N=2500时，GPU明显优于CPU。我们的结果表明，应该对GPU实现进行沉积模拟测试。这里考虑的实现可以用于任何可以使用显式方法来近似演化的沉积。

虚拟储存加速：CPU和GPU的案例研究——耦合自旋转矩振荡器储存