def test_FinNumbaNumbaParallel(useSobol): valueDate = FinDate(1, 1, 2015) expiryDate = FinDate(1, 7, 2015) stockPrice = 100 volatility = 0.30 interestRate = 0.05 dividendYield = 0.01 seed = 2021 model = FinModelBlackScholes(volatility) discountCurve = FinDiscountCurveFlat(valueDate, interestRate) useSobolInt = int(useSobol) testCases.header("NUMPATHS", "VALUE_BS", "VALUE_MC", "TIME") callOption = FinEquityVanillaOption(expiryDate, 100.0, FinOptionTypes.EUROPEAN_CALL) value = callOption.value(valueDate, stockPrice, discountCurve, dividendYield, model) numPoints = 20 v_exact = [value] * numPoints numPathsList = np.arange(1, numPoints + 1, 1) * 1000000 NUMBA_ONLY_v = [] NUMBA_ONLY_t = [] print("NUMBA ONLY") for numPaths in numPathsList: start = time.time() valueMC = callOption.valueMC_NUMBA_ONLY(valueDate, stockPrice, discountCurve, dividendYield, model, numPaths, seed, useSobolInt) end = time.time() duration = end - start print("%10d %9.5f %9.5f %9.6f" % (numPaths, value, valueMC, duration)) NUMBA_ONLY_v.append(valueMC) NUMBA_ONLY_t.append(duration) NUMBA_PARALLEL_v = [] NUMBA_PARALLEL_t = [] print("NUMBA PARALLEL") for numPaths in numPathsList: start = time.time() valueMC = callOption.valueMC_NUMBA_PARALLEL(valueDate, stockPrice, discountCurve, dividendYield, model, numPaths, seed, useSobolInt) end = time.time() duration = end - start print("%10d %9.5f %9.5f %9.6f" % (numPaths, value, valueMC, duration)) NUMBA_PARALLEL_v.append(valueMC) NUMBA_PARALLEL_t.append(duration) ########################################################################### import matplotlib.pyplot as plt if useSobol: title = "SOBOL: NUMBA VS NUMBA + PARALLEL" else: title = "PSEUDORANDOM: NUMBA VS NUMBA + PARALLEL" plt.figure(figsize=(8, 6)) plt.plot(numPathsList, NUMBA_ONLY_t, 'o-', label="NUMBA ONLY") plt.plot(numPathsList, NUMBA_PARALLEL_t, 'o-', label="NUMBA PARALLEL") plt.xlabel("Number of Paths") plt.ylabel("Wall Time (s)") plt.legend() plt.title(title) plt.figure(figsize=(8, 6)) plt.plot(numPathsList, v_exact, label="EXACT") plt.plot(numPathsList, NUMBA_ONLY_v, 'o-', label="NUMBA ONLY") plt.plot(numPathsList, NUMBA_PARALLEL_v, 'o-', label="NUMBA PARALLEL") plt.xlabel("Number of Paths") plt.ylabel("Option Value") plt.legend() plt.title(title)
def test_FinNumbaNumpySpeed(useSobol): valueDate = FinDate(1, 1, 2015) expiryDate = FinDate(1, 7, 2015) stockPrice = 100 volatility = 0.30 interestRate = 0.05 dividendYield = 0.01 seed = 1999 model = FinModelBlackScholes(volatility) discountCurve = FinDiscountCurveFlat(valueDate, interestRate) useSobolInt = int(useSobol) testCases.header("NUMPATHS", "VALUE_BS", "VALUE_MC", "TIME") callOption = FinEquityVanillaOption(expiryDate, 100.0, FinOptionTypes.EUROPEAN_CALL) value = callOption.value(valueDate, stockPrice, discountCurve, dividendYield, model) numPoints = 20 v_exact = [value] * numPoints ########################################################################### # DO UP TO 100K AS IT IS SLOW ########################################################################### numPathsList = np.arange(1, numPoints + 1, 1) * 100000 NONUMBA_NONUMPY_v = [] NONUMBA_NONUMPY_t = [] print("PURE PYTHON") for numPaths in numPathsList: start = time.time() valueMC = callOption.valueMC_NONUMBA_NONUMPY(valueDate, stockPrice, discountCurve, dividendYield, model, numPaths, seed, useSobolInt) end = time.time() duration = end - start print("%10d %9.5f %9.5f %9.6f" % (numPaths, value, valueMC, duration)) NONUMBA_NONUMPY_v.append(valueMC) NONUMBA_NONUMPY_t.append(duration + 1e-10) NUMPY_ONLY_v = [] NUMPY_ONLY_t = [] print("NUMPY ONLY") for numPaths in numPathsList: start = time.time() valueMC = callOption.valueMC_NUMPY_ONLY(valueDate, stockPrice, discountCurve, dividendYield, model, numPaths, seed, useSobolInt) end = time.time() duration = end - start print("%10d %9.5f %9.5f %9.6f" % (numPaths, value, valueMC, duration)) NUMPY_ONLY_v.append(valueMC) NUMPY_ONLY_t.append(duration + 1e-10) # speedUp = np.array(NONUMBA_NONUMPY_t)/np.array(NUMPY_ONLY_t) # print(NUMPY_ONLY_t) # print(NONUMBA_NONUMPY_t) # print(speedUp) if useSobol: title = "SOBOL: PURE PYTHON VS NUMPY" else: title = "PSEUDORANDOM: PURE PYTHON VS NUMPY" plt.figure(figsize=(8, 6)) plt.plot(numPathsList, NONUMBA_NONUMPY_t, 'o-', label="PURE PYTHON") plt.plot(numPathsList, NUMPY_ONLY_t, 'o-', label="NUMPY ONLY") plt.xlabel("Number of Paths") plt.ylabel("Wall Time (s)") plt.legend() plt.title(title) plt.figure(figsize=(8, 6)) plt.plot(numPathsList, v_exact, label="EXACT") plt.plot(numPathsList, NONUMBA_NONUMPY_v, 'o-', label="PURE PYTHON") plt.plot(numPathsList, NUMPY_ONLY_v, 'o-', label="NUMPY ONLY") plt.xlabel("Number of Paths") plt.ylabel("Option Value") plt.legend() plt.title(title) ########################################################################### # DO UP TO 10 MILLION NOW THAT WE HAVE NUMPY ########################################################################### numPathsList = np.arange(1, numPoints + 1, 1) * 1000000 NUMPY_ONLY_v = [] NUMPY_ONLY_t = [] print("NUMPY ONLY") for numPaths in numPathsList: start = time.time() valueMC = callOption.valueMC_NUMPY_ONLY(valueDate, stockPrice, discountCurve, dividendYield, model, numPaths, seed, useSobolInt) end = time.time() duration = end - start print("%10d %9.5f %9.5f %9.6f" % (numPaths, value, valueMC, duration)) NUMPY_ONLY_v.append(valueMC) NUMPY_ONLY_t.append(duration) NUMBA_NUMPY_v = [] NUMBA_NUMPY_t = [] print("NUMBA+NUMPY") for numPaths in numPathsList: start = time.time() valueMC = callOption.valueMC_NUMPY_NUMBA(valueDate, stockPrice, discountCurve, dividendYield, model, numPaths, seed, useSobolInt) end = time.time() duration = end - start print("%10d %9.5f %9.5f %9.6f" % (numPaths, value, valueMC, duration)) NUMBA_NUMPY_v.append(valueMC) NUMBA_NUMPY_t.append(duration) NUMBA_ONLY_v = [] NUMBA_ONLY_t = [] print("NUMBA ONLY") for numPaths in numPathsList: start = time.time() valueMC = callOption.valueMC_NUMBA_ONLY(valueDate, stockPrice, discountCurve, dividendYield, model, numPaths, seed, useSobolInt) end = time.time() duration = end - start print("%10d %9.5f %9.5f %9.6f" % (numPaths, value, valueMC, duration)) NUMBA_ONLY_v.append(valueMC) NUMBA_ONLY_t.append(duration) NUMBA_PARALLEL_v = [] NUMBA_PARALLEL_t = [] print("NUMBA PARALLEL") for numPaths in numPathsList: start = time.time() valueMC = callOption.valueMC_NUMBA_PARALLEL(valueDate, stockPrice, discountCurve, dividendYield, model, numPaths, seed, useSobolInt) end = time.time() duration = end - start print("%10d %9.5f %9.5f %9.6f" % (numPaths, value, valueMC, duration)) NUMBA_PARALLEL_v.append(valueMC) NUMBA_PARALLEL_t.append(duration) # speedUp = np.array(NUMBA_ONLY_t)/np.array(NUMBA_PARALLEL_t) # print("PARALLEL:", speedUp) ########################################################################### # COMPUTED USING NUMSTEPS FROM 1M to 10M ########################################################################### CPP_t = np.array([ 0.075, 0.155, 0.223, 0.313, 0.359, 0.421, 0.495, 0.556, 0.64, 0.702, 0.765, 0.841, 0.923, 0.982, 1.05, 1.125, 1.195, 1.261, 1.333, 1.408 ]) CPP_v = np.array([ 9.30872, 9.29576, 9.29422, 9.29832, 9.29863, 9.30153, 9.2994, 9.3025, 9.29653, 9.29875, 9.29897, 9.29996, 9.29931, 9.29796, 9.29784, 9.2992, 9.3001, 9.30093, 9.29876, 9.29921 ]) if useSobol: title = "SOBOL: COMPARING OPTIMISATIONS" else: title = "PSEUDORANDOM: COMPARING OPTIMISATIONS" plt.figure(figsize=(8, 6)) plt.plot(numPathsList, NUMPY_ONLY_t, 'o-', label="NUMPY ONLY") plt.plot(numPathsList, NUMBA_NUMPY_t, 'o-', label="NUMBA + NUMPY") plt.xlabel("Number of Paths") plt.ylabel("Wall Time (s)") plt.legend() plt.title(title) ########################################################################### if useSobol: title = "SOBOL: COMPARING OPTIMISATIONS" else: title = "PSEUDORANDOM: COMPARING OPTIMISATIONS" plt.figure(figsize=(8, 6)) plt.plot(numPathsList, NUMPY_ONLY_t, 'o-', label="NUMPY ONLY") plt.plot(numPathsList, NUMBA_NUMPY_t, 'o-', label="NUMBA + NUMPY") plt.plot(numPathsList, NUMBA_ONLY_t, 'o-', label="NUMBA ONLY") plt.plot(numPathsList, NUMBA_PARALLEL_t, 'o-', label="NUMBA PARALLEL") if useSobol == False: plt.plot(numPathsList, CPP_t, 'o-', label="C++") plt.xlabel("Number of Paths") plt.ylabel("Wall Time (s)") plt.legend() plt.title(title) ########################################################################### plt.figure(figsize=(8, 6)) plt.plot(numPathsList, v_exact, label="EXACT") plt.plot(numPathsList, NUMBA_ONLY_v, 'o-', label="NUMBA ONLY") plt.plot(numPathsList, CPP_v, 'o-', label="C++") plt.xlabel("Number of Paths") plt.ylabel("Option Value") plt.legend() plt.title(title)