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457 lines
12 KiB
Plaintext
457 lines
12 KiB
Plaintext
/* Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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* * Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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* * Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in the
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* documentation and/or other materials provided with the distribution.
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* * Neither the name of NVIDIA CORPORATION nor the names of its
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* contributors may be used to endorse or promote products derived
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* from this software without specific prior written permission.
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*
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* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS ``AS IS'' AND ANY
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* EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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* IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
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* PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
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* CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
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* EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
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* PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
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* PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
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* OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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* (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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* OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*/
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#include <stdio.h>
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#include "helper_cuda.h"
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#include "Mandelbrot_kernel.h"
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// The dimensions of the thread block
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#define BLOCKDIM_X 16
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#define BLOCKDIM_Y 16
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#define ABS(n) ((n) < 0 ? -(n) : (n))
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// Double single functions based on DSFUN90 package:
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// http://crd.lbl.gov/~dhbailey/mpdist/index.html
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// This function sets the DS number A equal to the double precision floating
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// point number B.
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inline void dsdeq(float &a0, float &a1, double b) {
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a0 = (float)b;
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a1 = (float)(b - a0);
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} // dsdcp
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// This function sets the DS number A equal to the single precision floating
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// point number B.
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__device__ inline void dsfeq(float &a0, float &a1, float b) {
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a0 = b;
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a1 = 0.0f;
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} // dsfeq
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// This function computes c = a + b.
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__device__ inline void dsadd(float &c0, float &c1, const float a0,
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const float a1, const float b0, const float b1) {
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// Compute dsa + dsb using Knuth's trick.
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float t1 = a0 + b0;
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float e = t1 - a0;
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float t2 = ((b0 - e) + (a0 - (t1 - e))) + a1 + b1;
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// The result is t1 + t2, after normalization.
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c0 = e = t1 + t2;
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c1 = t2 - (e - t1);
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} // dsadd
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// This function computes c = a - b.
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__device__ inline void dssub(float &c0, float &c1, const float a0,
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const float a1, const float b0, const float b1) {
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// Compute dsa - dsb using Knuth's trick.
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float t1 = a0 - b0;
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float e = t1 - a0;
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float t2 = ((-b0 - e) + (a0 - (t1 - e))) + a1 - b1;
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// The result is t1 + t2, after normalization.
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c0 = e = t1 + t2;
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c1 = t2 - (e - t1);
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} // dssub
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#if 1
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// This function multiplies DS numbers A and B to yield the DS product C.
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__device__ inline void dsmul(float &c0, float &c1, const float a0,
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const float a1, const float b0, const float b1) {
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// This splits dsa(1) and dsb(1) into high-order and low-order words.
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float cona = a0 * 8193.0f;
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float conb = b0 * 8193.0f;
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float sa1 = cona - (cona - a0);
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float sb1 = conb - (conb - b0);
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float sa2 = a0 - sa1;
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float sb2 = b0 - sb1;
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// Multilply a0 * b0 using Dekker's method.
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float c11 = a0 * b0;
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float c21 = (((sa1 * sb1 - c11) + sa1 * sb2) + sa2 * sb1) + sa2 * sb2;
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// Compute a0 * b1 + a1 * b0 (only high-order word is needed).
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float c2 = a0 * b1 + a1 * b0;
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// Compute (c11, c21) + c2 using Knuth's trick, also adding low-order product.
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float t1 = c11 + c2;
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float e = t1 - c11;
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float t2 = ((c2 - e) + (c11 - (t1 - e))) + c21 + a1 * b1;
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// The result is t1 + t2, after normalization.
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c0 = e = t1 + t2;
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c1 = t2 - (e - t1);
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} // dsmul
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#else
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// Modified double-single mul function by Norbert Juffa, NVIDIA
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// uses __fmul_rn() and __fadd_rn() intrinsics which prevent FMAD merging
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/* Based on: Guillaume Da Gra<72>a, David Defour. Implementation of Float-Float
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* Operators on Graphics Hardware. RNC'7 pp. 23-32, 2006.
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*/
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// This function multiplies DS numbers A and B to yield the DS product C.
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__device__ inline void dsmul(float &c0, float &c1, const float a0,
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const float a1, const float b0, const float b1) {
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// This splits dsa(1) and dsb(1) into high-order and low-order words.
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float cona = a0 * 8193.0f;
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float conb = b0 * 8193.0f;
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float sa1 = cona - (cona - a0);
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float sb1 = conb - (conb - b0);
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float sa2 = a0 - sa1;
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float sb2 = b0 - sb1;
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// Multilply a0 * b0 using Dekker's method.
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float c11 = __fmul_rn(a0, b0);
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float c21 = (((sa1 * sb1 - c11) + sa1 * sb2) + sa2 * sb1) + sa2 * sb2;
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// Compute a0 * b1 + a1 * b0 (only high-order word is needed).
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float c2 = __fmul_rn(a0, b1) + __fmul_rn(a1, b0);
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// Compute (c11, c21) + c2 using Knuth's trick, also adding low-order product.
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float t1 = c11 + c2;
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float e = t1 - c11;
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float t2 = ((c2 - e) + (c11 - (t1 - e))) + c21 + __fmul_rn(a1, b1);
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// The result is t1 + t2, after normalization.
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c0 = e = t1 + t2;
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c1 = t2 - (e - t1);
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} // dsmul
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#endif
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// The core Mandelbrot CUDA GPU calculation function
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#if 1
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// Unrolled version
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template <class T>
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__device__ inline int CalcMandelbrot(const T xPos, const T yPos,
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const T xJParam, const T yJParam,
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const int crunch, const bool isJulia) {
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T x, y, xx, yy;
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int i = crunch;
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T xC, yC;
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if (isJulia) {
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xC = xJParam;
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yC = yJParam;
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y = yPos;
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x = xPos;
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yy = y * y;
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xx = x * x;
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} else {
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xC = xPos;
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yC = yPos;
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y = 0;
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x = 0;
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yy = 0;
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xx = 0;
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}
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do {
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// Iteration 1
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if (xx + yy > T(4.0)) return i - 1;
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y = x * y * T(2.0) + yC;
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x = xx - yy + xC;
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yy = y * y;
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xx = x * x;
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// Iteration 2
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if (xx + yy > T(4.0)) return i - 2;
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y = x * y * T(2.0) + yC;
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x = xx - yy + xC;
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yy = y * y;
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xx = x * x;
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// Iteration 3
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if (xx + yy > T(4.0)) return i - 3;
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y = x * y * T(2.0) + yC;
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x = xx - yy + xC;
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yy = y * y;
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xx = x * x;
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// Iteration 4
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if (xx + yy > T(4.0)) return i - 4;
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y = x * y * T(2.0) + yC;
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x = xx - yy + xC;
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yy = y * y;
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xx = x * x;
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// Iteration 5
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if (xx + yy > T(4.0)) return i - 5;
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y = x * y * T(2.0) + yC;
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x = xx - yy + xC;
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yy = y * y;
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xx = x * x;
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// Iteration 6
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if (xx + yy > T(4.0)) return i - 6;
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y = x * y * T(2.0) + yC;
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x = xx - yy + xC;
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yy = y * y;
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xx = x * x;
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// Iteration 7
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if (xx + yy > T(4.0)) return i - 7;
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y = x * y * T(2.0) + yC;
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x = xx - yy + xC;
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yy = y * y;
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xx = x * x;
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// Iteration 8
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if (xx + yy > T(4.0)) return i - 8;
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y = x * y * T(2.0) + yC;
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x = xx - yy + xC;
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yy = y * y;
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xx = x * x;
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// Iteration 9
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if (xx + yy > T(4.0)) return i - 9;
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y = x * y * T(2.0) + yC;
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x = xx - yy + xC;
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yy = y * y;
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xx = x * x;
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// Iteration 10
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if (xx + yy > T(4.0)) return i - 10;
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y = x * y * T(2.0) + yC;
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x = xx - yy + xC;
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yy = y * y;
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xx = x * x;
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// Iteration 11
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if (xx + yy > T(4.0)) return i - 11;
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y = x * y * T(2.0) + yC;
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x = xx - yy + xC;
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yy = y * y;
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xx = x * x;
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// Iteration 12
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if (xx + yy > T(4.0)) return i - 12;
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y = x * y * T(2.0) + yC;
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x = xx - yy + xC;
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yy = y * y;
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xx = x * x;
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// Iteration 13
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if (xx + yy > T(4.0)) return i - 13;
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y = x * y * T(2.0) + yC;
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x = xx - yy + xC;
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yy = y * y;
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xx = x * x;
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// Iteration 14
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if (xx + yy > T(4.0)) return i - 14;
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y = x * y * T(2.0) + yC;
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x = xx - yy + xC;
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yy = y * y;
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xx = x * x;
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// Iteration 15
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if (xx + yy > T(4.0)) return i - 15;
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y = x * y * T(2.0) + yC;
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x = xx - yy + xC;
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yy = y * y;
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xx = x * x;
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// Iteration 16
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if (xx + yy > T(4.0)) return i - 16;
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y = x * y * T(2.0) + yC;
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x = xx - yy + xC;
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yy = y * y;
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xx = x * x;
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// Iteration 17
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if (xx + yy > T(4.0)) return i - 17;
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y = x * y * T(2.0) + yC;
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x = xx - yy + xC;
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yy = y * y;
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xx = x * x;
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// Iteration 18
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if (xx + yy > T(4.0)) return i - 18;
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y = x * y * T(2.0) + yC;
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x = xx - yy + xC;
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yy = y * y;
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xx = x * x;
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// Iteration 19
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if (xx + yy > T(4.0)) return i - 19;
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y = x * y * T(2.0) + yC;
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x = xx - yy + xC;
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yy = y * y;
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xx = x * x;
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// Iteration 20
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i -= 20;
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if ((i <= 0) || (xx + yy > T(4.0))) return i;
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y = x * y * T(2.0) + yC;
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x = xx - yy + xC;
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yy = y * y;
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xx = x * x;
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} while (1);
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} // CalcMandelbrot
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#else
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template <class T>
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__device__ inline int CalcMandelbrot(const T xPos, const T yPos,
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const T xJParam, const T yJParam,
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const int crunch, const isJulia) {
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T x, y, xx, yy, xC, yC;
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if (isJulia) {
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xC = xJParam;
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yC = yJParam;
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y = yPos;
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x = xPos;
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yy = y * y;
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xx = x * x;
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} else {
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xC = xPos;
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yC = yPos;
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y = 0;
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x = 0;
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yy = 0;
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xx = 0;
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}
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int i = crunch;
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while (--i && (xx + yy < T(4.0))) {
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y = x * y * T(2.0) + yC;
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x = xx - yy + xC;
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yy = y * y;
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xx = x * x;
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}
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return i; // i > 0 ? crunch - i : 0;
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} // CalcMandelbrot
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#endif
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// The core Mandelbrot calculation function in double-single precision
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__device__ inline int CalcMandelbrotDS(const float xPos0, const float xPos1,
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const float yPos0, const float yPos1,
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const float xJParam, const float yJParam,
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const int crunch, const bool isJulia) {
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float xx0, xx1;
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float yy0, yy1;
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float sum0, sum1;
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int i = crunch;
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float x0, x1, y0, y1;
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float xC0, xC1, yC0, yC1;
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if (isJulia) {
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xC0 = xJParam;
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xC1 = 0;
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yC0 = yJParam;
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yC1 = 0;
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y0 = yPos0; // y = yPos;
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y1 = yPos1;
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x0 = xPos0; // x = xPos;
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x1 = xPos1;
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dsmul(yy0, yy1, y0, y1, y0, y1); // yy = y * y;
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dsmul(xx0, xx1, x0, x1, x0, x1); // xx = x * x;
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} else {
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xC0 = xPos0;
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xC1 = xPos1;
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yC0 = yPos0;
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yC1 = yPos1;
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y0 = 0; // y = 0 ;
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y1 = 0;
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x0 = 0; // x = 0 ;
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x1 = 0;
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yy0 = 0; // yy = 0 ;
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yy1 = 0;
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xx0 = 0; // xx = 0 ;
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xx1 = 0;
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}
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dsadd(sum0, sum1, xx0, xx1, yy0, yy1); // sum = xx + yy;
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while (--i && (sum0 + sum1 < 4.0f)) {
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dsmul(y0, y1, x0, x1, y0, y1); // y = x * y * 2.0f + yC; // yC is yPos for
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// Mandelbrot and it is yJParam for Julia
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dsadd(y0, y1, y0, y1, y0, y1);
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dsadd(y0, y1, y0, y1, yC0, yC1);
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dssub(x0, x1, xx0, xx1, yy0, yy1); // x = xx - yy + xC; // xC is xPos for
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// Mandelbrot and it is xJParam for
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// Julia
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dsadd(x0, x1, x0, x1, xC0, xC1);
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dsmul(yy0, yy1, y0, y1, y0, y1); // yy = y * y;
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dsmul(xx0, xx1, x0, x1, x0, x1); // xx = x * x;
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dsadd(sum0, sum1, xx0, xx1, yy0, yy1); // sum = xx + yy;
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}
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return i;
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} // CalcMandelbrotDS
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// Determine if two pixel colors are within tolerance
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__device__ inline int CheckColors(const uchar4 &color0, const uchar4 &color1) {
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int x = color1.x - color0.x;
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int y = color1.y - color0.y;
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int z = color1.z - color0.z;
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return (ABS(x) > 10) || (ABS(y) > 10) || (ABS(z) > 10);
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} // CheckColors
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// Increase the grid size by 1 if the image width or height does not divide
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// evenly
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// by the thread block dimensions
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inline int iDivUp(int a, int b) {
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return ((a % b) != 0) ? (a / b + 1) : (a / b);
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} // iDivUp
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