557a245dd5
HIP RT enables AMD hardware ray tracing on RDNA2 and above, and falls back to a to shader implementation for older graphics cards. It offers an average 25% sample rendering rate improvement in Cycles benchmarks, on a W6800 card. The ray tracing feature functions are accessed through HIP RT SDK, available on GPUOpen. HIP RT traversal functionality is pre-compiled in bitcode format and shipped with the SDK. This is not yet enabled as there are issues to be resolved, but landing the code now makes testing and further changes easier. Known limitations: * Not working yet with current public AMD drivers. * Visual artifact in motion blur. * One of the buffers allocated for traversal has a static size. Allocating it dynamically would reduce memory usage. * This is for Windows only currently, no Linux support. Co-authored-by: Brecht Van Lommel <brecht@blender.org> Ref #105538
68 lines
2.5 KiB
C
68 lines
2.5 KiB
C
/* SPDX-License-Identifier: Apache-2.0
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* Copyright 2011-2022 Blender Foundation */
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/* Device data taken from HIP occupancy calculator.
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*
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* Terminology
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* - HIP GPUs have multiple streaming multiprocessors
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* - Each multiprocessor executes multiple thread blocks
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* - Each thread block contains a number of threads, also known as the block size
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* - Multiprocessors have a fixed number of registers, and the amount of registers
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* used by each threads limits the number of threads per block.
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*/
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/* Launch Bound Definitions */
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#define GPU_MULTIPRESSOR_MAX_REGISTERS 65536
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#define GPU_MULTIPROCESSOR_MAX_BLOCKS 64
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#define GPU_BLOCK_MAX_THREADS 1024
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#define GPU_THREAD_MAX_REGISTERS 255
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#define GPU_KERNEL_BLOCK_NUM_THREADS 1024
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#define GPU_KERNEL_MAX_REGISTERS 64
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/* For performance tuning of hiprt kernels we might have to change the number
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* that's why we don't use GPU_KERNEL_BLOCK_NUM_THREADS. */
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#define GPU_HIPRT_KERNEL_BLOCK_NUM_THREADS 1024
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/* Compute number of threads per block and minimum blocks per multiprocessor
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* given the maximum number of registers per thread. */
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#define ccl_gpu_kernel(block_num_threads, thread_num_registers) \
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extern "C" __global__ void __launch_bounds__(block_num_threads, \
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GPU_MULTIPRESSOR_MAX_REGISTERS / \
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(block_num_threads * thread_num_registers))
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#define ccl_gpu_kernel_threads(block_num_threads) \
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extern "C" __global__ void __launch_bounds__(block_num_threads)
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#define ccl_gpu_kernel_signature(name, ...) kernel_gpu_##name(__VA_ARGS__)
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#define ccl_gpu_kernel_postfix
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#define ccl_gpu_kernel_call(x) x
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#define ccl_gpu_kernel_within_bounds(i, n) ((i) < (n))
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/* Define a function object where "func" is the lambda body, and additional parameters are used to
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* specify captured state */
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#define ccl_gpu_kernel_lambda(func, ...) \
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struct KernelLambda { \
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__VA_ARGS__; \
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__device__ int operator()(const int state) \
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{ \
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return (func); \
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} \
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} ccl_gpu_kernel_lambda_pass
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/* sanity checks */
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#if GPU_KERNEL_BLOCK_NUM_THREADS > GPU_BLOCK_MAX_THREADS
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# error "Maximum number of threads per block exceeded"
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#endif
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#if GPU_MULTIPRESSOR_MAX_REGISTERS / (GPU_KERNEL_BLOCK_NUM_THREADS * GPU_KERNEL_MAX_REGISTERS) > \
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GPU_MULTIPROCESSOR_MAX_BLOCKS
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# error "Maximum number of blocks per multiprocessor exceeded"
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#endif
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#if GPU_KERNEL_MAX_REGISTERS > GPU_THREAD_MAX_REGISTERS
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# error "Maximum number of registers per thread exceeded"
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#endif
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