Battlestars

We implemented four kernels for the Helion challenge on NVIDIA B200 GPUs, prioritizing FP32 accumulation for precision and 3D tiling for better hardware occupancy. causal_conv1d: This is a causal depthwise 1D convolution used in Mamba and Mamba-2 architectures. We optimized this by using F.pad before the kernel launch and caching the weights and bias in the SRAM (the GPU's fast on-chip memory) and Registers. This resulted in execution times ranging from 0.03ms to 0.09ms on the B200. gated_deltanet_chunk_fwd_h: This kernel handles the inter-chunk state recurrence. We achieved performance gains by removing redundant hl.dot (matrix multiplication) calls and streamlining the math used for the gating mechanism. It runs in 0.005ms to 0.08ms. gated_deltanet_chunk_fwd_o: This kernel computes the final output. We utilized B200-specific Advanced Control Files (ACFs) to tune hardware parameters and implemented lazy-compilation to avoid timing out on the 12-minute leaderboard limit. Performance ranges from 0.02ms to 0.06ms. gated_deltanet_recompute_w_u: This handles the forward WY-transform. We achieved a speedup by vectorizing the matrix multiplications (processing multiple data points at once) and scaling the K and V vectors before performing a single hl.dot pass. This takes 0.13ms to 0.36ms. Take a look at our cool dashboard in the repo for screenshots and instructions on how to run it! :)