Compare packages added.

plot_scripts/plot_display_com_cap.py

@@ -0,0 +1,103 @@
+import numpy as np
+import h5py
+import os
+
+import mercury as mr
+
+import sys
+sys.path.append('/plot_scripts/')
+from map_packages_colors_1v1 import *
+from plot_scripts_1v1 import *
+
+# package_str = ['qiskit' , 'cirq', 'qsimcirq', 'pennylane', 'pennylane_l', 'qibo', 'qibojit', 'yao', 'quest', 'qulacs', 'intel_qs_cpp', 'projectq', 'svsim',  'hybridq', 'hiq', 'qcgpu', 'qrack_sch', 'cuquantum_qiskit', 'cuquantum_qsimcirq', 'qpanda']
+
+
+def abs_time_pack(task, package, pr, N_end):
+
+    if task == "Heisenberg dynamics":
+        task = "hdyn"
+    elif task == "Random Quantum Circuit":
+        task = "rqc"
+    elif task == "Quantum Fourier Transform":
+        task = "qft"
+
+    if pr == "Single":
+        pr = "sp"
+    elif pr == "Double":
+        pr = "dp"
+
+    fig, ax = plt.subplots()
+
+    dir = os.getcwd()
+
+    if task == 'hdyn' or task == 'qft':
+        N_arr = np.arange(6, N_end, 2)
+    elif task == 'rqc':
+        N_arr = np.arange(12, N_end, 2)
+
+
+    dat_fst = dir + '/data/{}/{}_singlethread_{}.h5'.format(task, package, pr)
+    dat_fmt = dir + '/data/{}/{}_multithread_{}.h5'.format(task, package, pr)
+    dat_fgpu = dir + '/data/{}/{}_gpu_{}.h5'.format(task, package, pr)
+
+    if not os.path.isfile(dat_fst) and not os.path.isfile(dat_fmt) and not os.path.isfile(dat_fgpu):
+        return mr.Md(f"Precision {pr} possibly not supported")
+
+    mr.Md(f"TtS performance of simulation packages with different compute capabilities")
+
+    if os.path.isfile(dat_fst):
+        h5f_st = h5py.File(dat_fst, 'r')
+        dat_st = h5f_st[storage_dict[package]][:]
+        h5f_st.close()
+        plot_abs_data_n_arr(N_arr, dat_st, package+'_'+task+'_singlethread_'+pr)
+
+    if os.path.isfile(dat_fmt):
+        h5f_mt = h5py.File(dat_fmt, 'r')
+        dat_mt = h5f_mt[storage_dict[package]][:]
+        h5f_mt.close()
+        plot_abs_data_n_arr(N_arr, dat_mt, package+'_'+task+'_multithread_'+pr)
+
+    if os.path.isfile(dat_fgpu):
+        h5f_gpu = h5py.File(dat_fgpu, 'r')
+        dat_gpu = h5f_gpu[storage_dict[package]][:]
+        h5f_gpu.close()
+        plot_abs_data_n_arr(N_arr, dat_gpu, package+'_'+task+'_gpu_'+pr)
+
+    gen_settings(fig, ax, r"N (system size)", r"Time ($t_{package}$)", False, True, True, N_arr[0]-2, N_arr[-1], True, 10**-1, 10**5, "out", None)
+
+    mr.Md("___")
+    mr.Md(f"Relative performance to singlethread performance")
+
+    fig, ax = plt.subplots()
+
+    if os.path.isfile(dat_fst) and os.path.isfile(dat_fmt):
+        plot_comp_data_n_arr(N_arr, dat_st, dat_st, package+'_'+task+'_singlethread_'+pr)
+        plot_comp_data_n_arr(N_arr, dat_st, dat_mt, package+'_'+task+'_multithread_'+pr)
+
+    if os.path.isfile(dat_fst) and os.path.isfile(dat_fgpu):
+        plot_comp_data_n_arr(N_arr, dat_st, dat_gpu, package+'_'+task+'_gpu_'+pr)
+
+    gen_settings(fig, ax, r"N (system size)", r"Relative to singlethread", False, True, True, N_arr[0]-2, N_arr[-1], True, 10**-1, 10**3, "out", None)
+
+    mr.Md("___")
+    mr.Md(f"Relative performance to multithread performance")
+
+    fig, ax = plt.subplots()
+
+    if os.path.isfile(dat_fmt) and os.path.isfile(dat_fgpu):
+        plot_comp_data_n_arr(N_arr, dat_mt, dat_gpu, package+'_'+task+'_gpu_'+pr)
+        plot_comp_data_n_arr(N_arr, dat_mt, dat_mt, package+'_'+task+'_multithread_'+pr)
+
+    gen_settings(fig, ax, r"N (system size)", r"Relative to multithread", False, True, True, N_arr[0]-2, N_arr[-1], True, 10**-1, 10**2, "out", None)
+
+    # else:
+    #     print(" Re-select the options as the requested option data is not available.")
+
+# pkg_str = ['qiskit' , 'cirq', 'qsimcirq', 'pennylane', 'pennylane_l', 'qibo', 'qibojit', 'yao', 'quest', 'qulacs', 'intel_qs_cpp', 'projectq', 'svsim',  'hybridq', 'hiq', 'qcgpu', 'qrack_sch']
+
+# abs_time_pack("Heisenberg dynamics", 'qsimcirq', 'Double', 36)
+
+# abs_time(pkg_str, task_1, p_com_cap, p_prec)
+# abs_time("Heisenberg dynamics", "Singlethread", "Single", 'qsimcirq')
+# abs_time_pack("Heisenberg dynamics", "Random Quantum Circuit", "Singlethread", "Single", 34)
+# abs_time_pack("Heisenberg dynamics", "Quantum Fourier Transform", "GPU", "Single", 38)

plot_scripts/plot_display_com_cap_all.py

@@ -0,0 +1,224 @@
+import numpy as np
+import h5py
+import os
+
+import mercury as mr
+
+import sys
+sys.path.append('/plot_scripts/')
+from map_packages_colors_all import *
+from plot_scripts_all import *
+
+package_str = ['qiskit' , 'cirq', 'qsimcirq', 'pennylane', 'pennylane_l', 'qibo', 'qibojit', 'yao', 'quest', 'qulacs', 'intel_qs_cpp', 'projectq', 'svsim',  'hybridq', 'hiq', 'qcgpu', 'qrack_sch', 'cuquantum_qiskit', 'cuquantum_qsimcirq', 'qpanda']
+
+
+def _build_data_mat(task, cc_1, cc_2, pr, _n_arr):
+
+    dir = os.getcwd()
+
+    data_mat = np.zeros((len(package_str), len(_n_arr)))
+
+    for p_i, pack in enumerate(package_str):
+
+        dat_cc1 = dir + '/data/{}/{}_{}_{}.h5'.format(task, pack, cc_1, pr)
+        dat_cc2 = dir + '/data/{}/{}_{}_{}.h5'.format(task, pack, cc_2, pr)
+
+        if os.path.isfile(dat_cc1) and os.path.isfile(dat_cc2):
+
+            h5f_cc1 = h5py.File(dat_cc1, 'r')
+            dat_cc1 = h5f_cc1[storage_dict[pack]][:]
+            h5f_cc1.close()
+
+            h5f_cc2 = h5py.File(dat_cc2, 'r')
+            dat_cc2 = h5f_cc2[storage_dict[pack]][:]
+            h5f_cc2.close()
+
+            ratio_arr = []
+
+            if len(dat_cc1) == len(dat_cc2):
+                for i, elem in enumerate(dat_cc1):
+                    ratio_arr.append(elem/float(dat_cc2[i]))
+            elif len(dat_cc1) > len(dat_cc2):
+                for i, elem in enumerate(dat_cc2):
+                    ratio_arr.append(dat_cc1[i]/float(elem))
+            elif len(dat_cc2) > len(dat_cc1):
+                for i, elem in enumerate(dat_cc1):
+                    ratio_arr.append(elem/float(dat_cc2[i]))
+
+            if len(_n_arr) > len(ratio_arr):
+                for r_i, rat in enumerate(ratio_arr):
+                    data_mat[p_i, r_i] = rat
+            elif len(_n_arr) < len(ratio_arr):
+                for n_i in range(len(_n_arr)):
+                    data_mat[p_i, n_i] = ratio_arr[n_i]
+            else:
+                for ri, rat_v in enumerate(ratio_arr):
+                    data_mat[p_i, ri] = rat_v
+
+    return data_mat
+
+def abs_time_pack(task, pr, N_end, cc_1, cc_2):
+
+    if task == "Heisenberg dynamics":
+        task = "hdyn"
+    elif task == "Random Quantum Circuit":
+        task = "rqc"
+    elif task == "Quantum Fourier Transform":
+        task = "qft"
+
+    if cc_1 == "Singlethread":
+        cc_1 = 'singlethread'
+    elif cc_1 == "Multithread":
+        cc_1 = 'multithread'
+    elif cc_1 == "GPU":
+        cc_1 = 'gpu'
+
+    if cc_2 == "Singlethread":
+        cc_2 = 'singlethread'
+    elif cc_2 == "Multithread":
+        cc_2 = 'multithread'
+    elif cc_2 == "GPU":
+        cc_2 = 'gpu'
+
+    if pr == "Single":
+        pr = "sp"
+    elif pr == "Double":
+        pr = "dp"
+
+    fig, ax = plt.subplots()
+
+    dir = os.getcwd()
+
+    if task == 'hdyn' or task == 'qft':
+        N_arr = np.arange(6, N_end, 2)
+    elif task == 'rqc':
+        N_arr = np.arange(12, N_end, 2)
+
+    # if not os.path.isfile(dat_fst) and not os.path.isfile(dat_fmt) and not os.path.isfile(dat_fgpu):
+    #     return mr.Md(f"Precision {pr} possibly not supported")
+
+    data_mat = _build_data_mat(task, cc_1, cc_2, pr, N_arr)
+
+    # params = {'figure.figsize': (10, 10)}
+    # plt.rcParams.update(params)
+    plt.imshow(data_mat, cmap='OrRd')#, vmin=-16, vmax=0)
+
+    plt.yticks(range(len(pkg_str)), package_str)
+    locs, labels = plt.yticks()
+
+    # plt.setp(labels, rotation=90)
+    plt.xticks(range(len(N_arr)), N_arr)
+    # locs, labels = plt.xticks()
+
+    ax.xaxis.set_major_locator(ticker.AutoLocator())
+    ax.xaxis.set_minor_locator(ticker.AutoMinorLocator())
+
+    plt.colorbar()
+    plt.tight_layout()
+    # plt.savefig(fn)
+    plt.show()
+
+# abs_time_pack("Heisenberg dynamics", "Double", 36, "Singlethread", "Multithread")
+# abs_time_pack("Random Quantum Circuit", "Double", 36, "Singlethread", "Multithread")
+
+def comp_time_pack(task_1, task_2, pr, N_end, cc_1, cc_2):
+
+    if task_1 == "Heisenberg dynamics":
+        task_1 = "hdyn"
+    elif task_1 == "Random Quantum Circuit":
+        task_1 = "rqc"
+    elif task_1 == "Quantum Fourier Transform":
+        task_1 = "qft"
+
+    if task_2 == "Heisenberg dynamics":
+        task_2 = "hdyn"
+    elif task_2 == "Random Quantum Circuit":
+        task_2 = "rqc"
+    elif task_2 == "Quantum Fourier Transform":
+        task_2 = "qft"
+
+    if cc_1 == "Singlethread":
+        cc_1 = 'singlethread'
+    elif cc_1 == "Multithread":
+        cc_1 = 'multithread'
+    elif cc_1 == "GPU":
+        cc_1 = 'gpu'
+
+    if cc_2 == "Singlethread":
+        cc_2 = 'singlethread'
+    elif cc_2 == "Multithread":
+        cc_2 = 'multithread'
+    elif cc_2 == "GPU":
+        cc_2 = 'gpu'
+
+    if pr == "Single":
+        pr = "sp"
+    elif pr == "Double":
+        pr = "dp"
+
+    fig, ax = plt.subplots()
+
+
+    dir = os.getcwd()
+
+    if task_1 == 'hdyn' or task_1 == 'qft':
+        N_arr_1 = np.arange(6, N_end, 2)
+    elif task_1 == 'rqc':
+        N_arr_1 = np.arange(12, N_end, 2)
+
+    if task_2 == 'hdyn' or task_2 == 'qft':
+        N_arr_2 = np.arange(6, N_end, 2)
+    elif task_2 == 'rqc':
+        N_arr_2 = np.arange(12, N_end, 2)
+
+    data_mat_1 = np.matrix(_build_data_mat(task_1, cc_1, cc_2, pr, N_arr_1))
+    data_mat_2 = np.matrix(_build_data_mat(task_2, cc_1, cc_2, pr, N_arr_2))
+
+    if N_arr_1[0] > N_arr_2[0]:
+        data_mat_2 = data_mat_2[:,3:]
+
+    elif N_arr_1[0] < N_arr_2[0]:
+        data_mat_1 = data_mat_1[:,3:]
+
+    # print(data_mat_1.shape)
+    # print(data_mat_2.shape)
+
+    # plt.imshow(data_mat_1, cmap='OrRd')#, vmin=-16, vmax=0)
+    # plt.show()
+    # plt.imshow(data_mat_2, cmap='OrRd')#, vmin=-16, vmax=0)
+    # plt.show()
+
+    comp_data_mat = np.zeros(data_mat_1.shape)
+
+    for ri in range(comp_data_mat.shape[0]):
+        for ci in range(comp_data_mat.shape[1]):
+            comp_data_mat[ri, ci] = data_mat_1[ri, ci]/data_mat_2[ri, ci]
+
+    # comp_data_mat = np.matrix(data_mat_1) - np.matrix(data_mat_2)
+
+    # params = {'figure.figsize': (10, 10)}
+    # plt.rcParams.update(params)
+
+    plt.imshow(comp_data_mat, cmap='Spectral')#, vmin=-16, vmax=0)
+
+    plt.yticks(range(len(pkg_str)), package_str)
+    locs, labels = plt.yticks()
+
+    # plt.setp(labels, rotation=90)
+    if N_arr_1[0] > N_arr_2[0]:
+        plt.xticks(range(len(N_arr_1)), N_arr_1)
+    elif N_arr_1[0] < N_arr_2[0]:
+        plt.xticks(range(len(N_arr_2)), N_arr_2)
+    else:
+        plt.xticks(range(len(N_arr_1)), N_arr_1)
+    # locs, labels = plt.xticks()
+
+    ax.xaxis.set_major_locator(ticker.AutoLocator())
+    ax.xaxis.set_minor_locator(ticker.AutoMinorLocator())
+
+    plt.colorbar()
+    plt.tight_layout()
+    # plt.savefig(fn)
+    plt.show()
+
+# comp_time_pack("Heisenberg dynamics", "Random Quantum Circuit", "Double", 36, "Singlethread", "Multithread")