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How to Build High-Performance GPU-Accelerated Simulations and Differentiable Physics Workflows Using NVIDIA Warp Kernels

angles = np.linspace(0.0, 2.0 * np.pi, n_particles, endpoint=False, dtype=np.float32) px0_np = 0.4 * np.cos(angles).astype(np.float32) py0_np = (0.7 + 0.15 * np.sin(angles)).astype(np.float32) vx0_np = (-0.8 * np.sin(angles)).astype(np.float32) vy0_np = (0.8 * np.cos(angles)).astype(np.float32) px0_wp = wp.array(px0_np, dtype=wp.float32, device=device) py0_wp = wp.array(py0_np, dtype=wp.float32,…

Moonshot AI Releases 𝑨𝒕𝒕𝒆𝒏𝒕𝒊𝒐𝒏 𝑹𝒆𝒔𝒊𝒅𝒖𝒂𝒍𝒔 to Replace Fixed Residual Mixing with Depth-Wise Attention for Better Scaling in Transformers

Residual connections are one of the least questioned parts of modern Transformer design. In PreNorm architectures, each layer adds its output back into a running hidden state, which keeps optimization stable and allows deep models to train. Moonshot AI researchers…