KernIt_Raj

Leaderboard name: bloomberg9383 All 5 kernels implemented in Helion DSL for Gated DeltaNet on B200: 1. fp8_quant: FP8 group quantization — computes per-group absmax and scales, quantizes to float8_e4m3fn. Straightforward elementwise kernel. 2. causal_conv1d: Causal depthwise 1D convolution — eliminated input padding by computing directly on raw input with clamped indices and validity masking, halving memory bandwidth. Uses [1,512] block tiling with 1 warp for maximum S-dimension coalescing. ~10.5μs geomean across benchmark shapes. 3. gated_deltanet_chunk_fwd_h: Inter-chunk state recurrence (h = decay * h + key^T * value) — sequential across chunks with hl.dot() matmuls. Autotuned per-shape configs with pointer indexing. 4. gated_deltanet_chunk_fwd_o: Intra/inter-chunk output computation with causal attention masking — uses hl.dot() for all matmuls (QK^T, attention*V, state contribution). Optimized with persistent_blocked scheduling, block_ptr indexing, and range flattening. ~17.7μs geomean. 5. gated_deltanet_recompute_w_u: WY-transform forward pass — parallel matmul-heavy kernel using hl.dot() for matrix products. Autotuned with per-shape block sizes and warp counts. Key optimizations: removed baseline redundant computations, replaced element-wise accumulation with hl.dot(), per-shape autotuned configs with static_shapes=True, persistent_blocked PID scheduling for L2 locality.