Ensure GPU code is optimized for both proper thread utilization and correct architecture dispatching: 1. **Maximize thread parallelism** - Design CUDA kernels to fully utilize available threads. When appropriate, use multi-dimensional grid configurations to parallelize across all relevant dimensions of your problem.
Ensure GPU code is optimized for both proper thread utilization and correct architecture dispatching:
// Instead of TODO comments like:
// TODO utilize more CUDA threads
// this will probably need some extra padding for warps
// Consider implementing a 2D grid approach:
dim3 block_dim(32, 8); // Thread block dimensions
dim3 grid_dim((n + block_dim.x - 1) / block_dim.x,
(padded_m + block_dim.y - 1) / block_dim.y);
kernel<<<grid_dim, block_dim>>>(...);
// Instead of compile-time only checks:
#if defined ENABLE_CUTLASS_MOE_SM100 && ENABLE_CUTLASS_MOE_SM100
if (version_num >= 100) { // Use runtime version check
cutlass_moe_mm_sm100(out_tensors, a_tensors, b_tensors, a_scales, b_scales,
expert_offsets, problem_sizes, a_strides, b_strides,
c_strides, per_act_token, per_out_ch);
return;
}
#endif
These approaches prevent performance bottlenecks and ensure code works correctly across different GPU hardware generations.
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