Differential D12888 Diff 43495 intern/cycles/kernel/kernel_random.h

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intern/cycles/kernel/kernel_random.h

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/* Skip initial numbers that for some dimensions have clear patterns that		/* Skip initial numbers that for some dimensions have clear patterns that
* don't cover the entire sample space. Ideally we would have a better		* don't cover the entire sample space. Ideally we would have a better
* progressive pattern that doesn't suffer from this problem, because even		* progressive pattern that doesn't suffer from this problem, because even
* with this offset some dimensions are quite poor.		* with this offset some dimensions are quite poor.
*/		*/
# define SOBOL_SKIP 64		# define SOBOL_SKIP 64

ccl_device uint sobol_dimension(ccl_global const KernelGlobals *kg, int index, int dimension)		ccl_device uint sobol_dimension(KernelGlobals kg, int index, int dimension)
{		{
uint result = 0;		uint result = 0;
uint i = index + SOBOL_SKIP;		uint i = index + SOBOL_SKIP;
for (int j = 0, x; (x = find_first_set(i)); i >>= x) {		for (int j = 0, x; (x = find_first_set(i)); i >>= x) {
j += x;		j += x;
result ^= __float_as_uint(kernel_tex_fetch(__sample_pattern_lut, 32 * dimension + j - 1));		result ^= __float_as_uint(kernel_tex_fetch(__sample_pattern_lut, 32 * dimension + j - 1));
}		}
return result;		return result;
}		}

#endif /* __SOBOL__ */		#endif /* __SOBOL__ */

ccl_device_forceinline float path_rng_1D(ccl_global const KernelGlobals *kg,		ccl_device_forceinline float path_rng_1D(KernelGlobals kg,
uint rng_hash,		uint rng_hash,
int sample,		int sample,
int dimension)		int dimension)
{		{
#ifdef __DEBUG_CORRELATION__		#ifdef __DEBUG_CORRELATION__
return (float)drand48();		return (float)drand48();
#endif		#endif

Show All 17 Lines	#ifdef __SOBOL__
*/		*/
uint tmp_rng = cmj_hash_simple(dimension, rng_hash);		uint tmp_rng = cmj_hash_simple(dimension, rng_hash);
shift = tmp_rng * (1.0f / (float)0xFFFFFFFF);		shift = tmp_rng * (1.0f / (float)0xFFFFFFFF);

return r + shift - floorf(r + shift);		return r + shift - floorf(r + shift);
#endif		#endif
}		}

ccl_device_forceinline void path_rng_2D(ccl_global const KernelGlobals *kg,		ccl_device_forceinline void path_rng_2D(KernelGlobals kg,
uint rng_hash,		uint rng_hash,
int sample,		int sample,
int dimension,		int dimension,
ccl_private float *fx,		ccl_private float *fx,
ccl_private float *fy)		ccl_private float *fy)
{		{
#ifdef __DEBUG_CORRELATION__		#ifdef __DEBUG_CORRELATION__
*fx = (float)drand48();		*fx = (float)drand48();
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{		{
const uint qx = 1103515245U * ((x >> 1U) ^ (y));		const uint qx = 1103515245U * ((x >> 1U) ^ (y));
const uint qy = 1103515245U * ((y >> 1U) ^ (x));		const uint qy = 1103515245U * ((y >> 1U) ^ (x));
const uint n = 1103515245U * ((qx) ^ (qy >> 3U));		const uint n = 1103515245U * ((qx) ^ (qy >> 3U));

return n;		return n;
}		}

ccl_device_inline uint path_rng_hash_init(ccl_global const KernelGlobals *ccl_restrict kg,		ccl_device_inline uint path_rng_hash_init(KernelGlobals kg,
const int sample,		const int sample,
const int x,		const int x,
const int y)		const int y)
{		{
const uint rng_hash = hash_iqnt2d(x, y) ^ kernel_data.integrator.seed;		const uint rng_hash = hash_iqnt2d(x, y) ^ kernel_data.integrator.seed;

#ifdef __DEBUG_CORRELATION__		#ifdef __DEBUG_CORRELATION__
srand48(rng_hash + sample);		srand48(rng_hash + sample);
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