IterationGenerator.cpp 8.0 KB

123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140141142143144145146147148149150151152153154155156157158159160161162163164165166167168169170171172173174175176177178179180181182183184185186187188189190191192193194195196197198199200201202203204205206207208209210211212213214215216217218219220221222223224225226227228229230231232233234235236237238239240241242243244245246247248249250251252253254255256257258259260261262263
  1. #include "IterationGenerator.h"
  2. #include "Mandel.h"
  3. #include "OpenClInternal.h"
  4. #include <omp.h>
  5. using mnd::IterationGenerator;
  6. using mnd::NaiveGenerator;
  7. using mnd::IterationFormula;
  8. IterationGenerator::IterationGenerator(IterationFormula z0, IterationFormula zi,
  9. mnd::Precision prec, mnd::CpuExtension ex) :
  10. mnd::MandelGenerator{ prec, ex },
  11. z0{ std::move(z0) },
  12. zi{ std::move(zi) }
  13. {
  14. }
  15. NaiveGenerator::NaiveGenerator(IterationFormula z0, IterationFormula zi,
  16. mnd::Precision prec, mnd::CpuExtension ex) :
  17. IterationGenerator{ std::move(z0), std::move(zi), prec, ex }
  18. {
  19. this->z0.optimize();
  20. this->zi.optimize();
  21. }
  22. void NaiveGenerator::generate(const mnd::MandelInfo& info, float* data)
  23. {
  24. const MandelViewport& view = info.view;
  25. const bool parallel = true;
  26. using T = double;
  27. T viewx = mnd::convert<T>(view.x);
  28. T viewy = mnd::convert<T>(view.y);
  29. T wpp = mnd::convert<T>(view.width / info.bWidth);
  30. T hpp = mnd::convert<T>(view.height / info.bHeight);
  31. #if defined(_OPENMP)
  32. if constexpr (parallel)
  33. omp_set_num_threads(omp_get_num_procs());
  34. # pragma omp parallel for schedule(static, 1) if (parallel)
  35. #endif
  36. for (long j = 0; j < info.bHeight; j++) {
  37. T y = viewy + T(double(j)) * hpp;
  38. for (long i = 0; i < info.bWidth; i++) {
  39. T x = viewx + T(double(i)) * wpp;
  40. T cx = x;
  41. T cy = y;
  42. std::complex<double> z = calc(*z0.expr, { 0, 0 }, { x, y });
  43. std::complex<double> c{ cx, cy };
  44. int k = 0;
  45. for (k = 0; k < info.maxIter; k++) {
  46. z = this->iterate(z, c);
  47. if (std::abs(z) >= 4)
  48. break;
  49. }
  50. data[i + j * info.bWidth] = float(k);
  51. /*if (info.smooth) {
  52. if (k >= info.maxIter)
  53. data[i + j * info.bWidth] = float(info.maxIter);
  54. else {
  55. float aapp = mnd::convert<float>(a);
  56. float bapp = mnd::convert<float>(b);
  57. data[i + j * info.bWidth] = ((float) k) + 1 - ::logf(::logf(aapp * aapp + bapp * bapp) / 2) / ::logf(2.0f);
  58. }
  59. }
  60. else
  61. data[i + j * info.bWidth] = k;*/
  62. }
  63. }
  64. }
  65. std::complex<double> NaiveGenerator::iterate(std::complex<double> z, std::complex<double> c)
  66. {
  67. auto& expr = *zi.expr;
  68. return calc(expr, z, c);
  69. }
  70. std::complex<double> NaiveGenerator::calc(mnd::Expression& expr, std::complex<double> z, std::complex<double> c)
  71. {
  72. std::complex<double> result = 0;
  73. std::visit([this, &result, z, c] (auto&& ex) {
  74. using T = std::decay_t<decltype(ex)>;
  75. if constexpr (std::is_same<T, mnd::Constant>::value) {
  76. result = std::complex{ mnd::convert<double>(ex.re), mnd::convert<double>(ex.im) };
  77. }
  78. else if constexpr (std::is_same<T, mnd::Variable>::value) {
  79. if (ex.name == "z")
  80. result = z;
  81. else if (ex.name == "c")
  82. result = c;
  83. else if (ex.name == "i")
  84. result = std::complex{ 0.0, 1.0 };
  85. }
  86. else if constexpr (std::is_same<T, mnd::Negation>::value) {
  87. result = -calc(*ex.operand, z, c);
  88. }
  89. else if constexpr (std::is_same<T, mnd::Addition>::value) {
  90. if (ex.subtraction)
  91. result = calc(*ex.left, z, c) - calc(*ex.right, z, c);
  92. else
  93. result = calc(*ex.left, z, c) + calc(*ex.right, z, c);
  94. }
  95. else if constexpr (std::is_same<T, mnd::Multiplication>::value) {
  96. result = calc(*ex.left, z, c) * calc(*ex.right, z, c);
  97. }
  98. else if constexpr (std::is_same<T, mnd::Division>::value) {
  99. result = calc(*ex.left, z, c) / calc(*ex.right, z, c);
  100. }
  101. else if constexpr (std::is_same<T, mnd::Pow>::value) {
  102. result = std::pow(calc(*ex.left, z, c), calc(*ex.right, z, c));
  103. }
  104. }, expr);
  105. return result;
  106. }
  107. #ifdef WITH_ASMJIT
  108. #if defined(__x86_64__) || defined(_M_X64)
  109. #include "ExecData.h"
  110. using mnd::CompiledGenerator;
  111. using mnd::CompiledGeneratorVec;
  112. CompiledGenerator::CompiledGenerator(std::unique_ptr<mnd::ExecData> execData,
  113. mnd::Precision prec, mnd::CpuExtension ex) :
  114. MandelGenerator{ prec, ex },
  115. execData{ std::move(execData) }
  116. {
  117. }
  118. CompiledGenerator::CompiledGenerator(CompiledGenerator&&) = default;
  119. CompiledGenerator::~CompiledGenerator(void)
  120. {
  121. }
  122. void CompiledGenerator::generate(const mnd::MandelInfo& info, float* data)
  123. {
  124. using IterFunc = int (*)(double, double, int);
  125. #if defined(_OPENMP)
  126. omp_set_num_threads(omp_get_num_procs());
  127. # pragma omp parallel for schedule(static, 1)
  128. #endif
  129. for (int i = 0; i < info.bHeight; i++) {
  130. double y = mnd::convert<double>(info.view.y + info.view.height * i / info.bHeight);
  131. for (int j = 0; j < info.bWidth; j++) {
  132. double x = mnd::convert<double>(info.view.x + info.view.width * j / info.bWidth);
  133. IterFunc iterFunc = asmjit::ptr_as_func<IterFunc>(this->execData->iterationFunc);
  134. int k = iterFunc(x, y, info.maxIter);
  135. data[i * info.bWidth + j] = float(k);
  136. }
  137. }
  138. }
  139. std::string CompiledGenerator::dump(void) const
  140. {
  141. asmjit::String d;
  142. execData->compiler->dump(d);
  143. return d.data();
  144. }
  145. CompiledGeneratorVec::CompiledGeneratorVec(std::unique_ptr<mnd::ExecData> execData) :
  146. CompiledGenerator{ std::move(execData), mnd::Precision::FLOAT, mnd::CpuExtension::X86_AVX }
  147. {
  148. }
  149. CompiledGeneratorVec::CompiledGeneratorVec(CompiledGeneratorVec&&) = default;
  150. CompiledGeneratorVec::~CompiledGeneratorVec(void)
  151. {
  152. }
  153. void CompiledGeneratorVec::generate(const mnd::MandelInfo& info, float* data)
  154. {
  155. using IterFunc = int (*)(float, float, float, int, float*);
  156. double dx = mnd::convert<double>(info.view.width / info.bWidth);
  157. #if defined(_OPENMP)
  158. omp_set_num_threads(omp_get_num_procs());
  159. # pragma omp parallel for schedule(static, 1)
  160. #endif
  161. for (int i = 0; i < info.bHeight; i++) {
  162. double y = mnd::convert<double>(info.view.y + info.view.height * i / info.bHeight);
  163. for (int j = 0; j < info.bWidth; j += 8) {
  164. double x = mnd::convert<double>(info.view.x + info.view.width * j / info.bWidth);
  165. float result[8];
  166. IterFunc iterFunc = asmjit::ptr_as_func<IterFunc>(this->execData->iterationFunc);
  167. int k = iterFunc(x, y, dx, info.maxIter-1, result);
  168. for (int k = 0; k < 8 && j + k < info.bWidth; k++)
  169. data[i * info.bWidth + j + k] = result[k];
  170. }
  171. }
  172. }
  173. #endif // defined(__x86_64__) || defined(_M_X64)
  174. #endif // WITH_ASMJIT
  175. #ifdef WITH_OPENCL
  176. using mnd::CompiledClGenerator;
  177. using mnd::CompiledClGeneratorDouble;
  178. CompiledClGenerator::CompiledClGenerator(mnd::MandelDevice& device, const std::string& code) :
  179. ClGeneratorFloat{ device, code }
  180. {
  181. kernel = cl::Kernel(program, "iterate");
  182. }
  183. void CompiledClGenerator::generate(const mnd::MandelInfo& info, float* data)
  184. {
  185. ::size_t bufferSize = info.bWidth * info.bHeight * sizeof(float);
  186. cl::Buffer buffer_A(context, CL_MEM_WRITE_ONLY, bufferSize);
  187. float pixelScaleX = float(info.view.width / info.bWidth);
  188. float pixelScaleY = float(info.view.height / info.bHeight);
  189. //static cl::Kernel iterate = cl::Kernel(program, "iterate");
  190. kernel.setArg(0, buffer_A);
  191. kernel.setArg(1, int(info.bWidth));
  192. kernel.setArg(2, float(info.view.x));
  193. kernel.setArg(3, float(info.view.y));
  194. kernel.setArg(4, float(pixelScaleX));
  195. kernel.setArg(5, float(pixelScaleY));
  196. kernel.setArg(6, int(info.maxIter));
  197. kernel.setArg(7, int(info.smooth ? 1 : 0));
  198. kernel.setArg(8, int(info.julia ? 1 : 0));
  199. kernel.setArg(9, float(info.juliaX));
  200. kernel.setArg(10, float(info.juliaY));
  201. queue.enqueueNDRangeKernel(kernel, 0, cl::NDRange(info.bWidth * info.bHeight));
  202. queue.enqueueReadBuffer(buffer_A, CL_TRUE, 0, bufferSize, data);
  203. }
  204. CompiledClGeneratorDouble::CompiledClGeneratorDouble(mnd::MandelDevice& device, const std::string& code) :
  205. ClGeneratorDouble{ device, code }
  206. {
  207. }
  208. #endif // WITH_OPENCL