github-actions[bot]
89 lines
3.0 KiB
Plaintext
89 lines
3.0 KiB
Plaintext
/**
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* @file configs.cuh
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* @brief Configuration constants and compile-time settings for ltx-kernels.
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*
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* This header defines the tunable parameters and constants used throughout
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* the ltx-kernels communication library. These values are chosen to balance
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* performance across different GPU architectures.
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*/
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#pragma once
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#include <cstdint>
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#include <cuda_bf16.h>
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#include <cuda_runtime.h>
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namespace ltx_kernels {
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// =============================================================================
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// Synchronization Configuration
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// =============================================================================
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/**
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* @brief Default barrier timeout in seconds.
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*
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* If a barrier wait exceeds this timeout, the kernel traps to indicate a deadlock or
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* communication failure. All2All converts it to clock cycles using the device's peak SM clock
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* (cudaDeviceGetAttribute(cudaDevAttrClockRate)), so the wall-clock guard holds regardless of GPU.
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*/
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constexpr double DEFAULT_BARRIER_TIMEOUT_SECONDS = 10.0;
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// =============================================================================
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// Hardware Limits
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// =============================================================================
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/**
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* @brief Maximum number of peer GPUs supported for IPC communication.
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*
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* This limits the size of static arrays for buffer pointers and barrier signals.
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* Set to 8 to support up to 8-way tensor parallelism (common for DGX systems).
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*/
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constexpr int MAX_NUM_PEERS = 8;
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// =============================================================================
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// Kernel Configuration
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// =============================================================================
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/**
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* @brief Default number of threads per block for All2All kernels.
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*
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* Used by send_recv_all2all and gather_heads kernels. The value 512 provides
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* good occupancy while leaving registers for complex pointer arithmetic.
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*/
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constexpr int DEFAULT_KERNEL_THREADS = 512;
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/**
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* @brief Number of threads per block for the AllGather kernel.
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*
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* AllGather uses more threads (1024) because its memory access pattern
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* is simpler (no head selection), allowing higher thread-level parallelism.
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*/
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constexpr int ALLGATHER_KERNEL_THREADS = 1024;
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} // namespace ltx_kernels
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// =============================================================================
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// Torch/CUDA Compatibility Fixes
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// =============================================================================
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/*
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* PyTorch sometimes disables CUDA half/bfloat16 operators and conversions
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* to avoid ambiguity in template resolution. We re-enable them here since
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* our kernels explicitly handle these types.
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*/
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#ifdef __CUDA_NO_HALF_CONVERSIONS__
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#undef __CUDA_NO_HALF_CONVERSIONS__
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#endif
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#ifdef __CUDA_NO_HALF_OPERATORS__
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#undef __CUDA_NO_HALF_OPERATORS__
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#endif
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#ifdef __CUDA_NO_HALF2_OPERATORS__
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#undef __CUDA_NO_HALF2_OPERATORS__
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#endif
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#ifdef __CUDA_NO_BFLOAT16_CONVERSIONS__
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#undef __CUDA_NO_BFLOAT16_CONVERSIONS__
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#endif
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#ifdef __CUDA_NO_BFLOAT162_OPERATORS__
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#undef __CUDA_NO_BFLOAT162_OPERATORS__
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#endif
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