09-2a fertig

05/05-2-multiprocess-with-gpu.py

@@ -0,0 +1,117 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+from multiprocessing import Pool
+from time import time
+import numpy as np
+from numba import njit
+
+start = time()
+
+seeds = np.ndarray([])  # 0
+seed_to_soil = []  # 1
+soil_to_fertilizer = []  # 2
+fertilizer_to_water = [] # 3
+water_to_light = []  # 4
+light_to_temperature = []  # 5
+temperature_to_humidity = []  # 6
+humidity_to_location = []  # 7
+
+list_number = 0
+# parse input
+input_file = open("input", "r")
+for line in input_file:
+    line = line.strip()
+    if line == "":
+        continue
+    if line.startswith('seeds: '):
+        seeds = [int(x) for x in line.replace('seeds: ', '').split()]
+    if line == "seed-to-soil map:":
+        list_number = 1
+        continue
+    if line == "soil-to-fertilizer map:":
+        list_number = 2
+        continue
+    if line == "fertilizer-to-water map:":
+        list_number = 3
+        continue
+    if line == "water-to-light map:":
+        list_number = 4
+        continue
+    if line == "light-to-temperature map:":
+        list_number = 5
+        continue
+    if line == "temperature-to-humidity map:":
+        list_number = 6
+        continue
+    if line == "humidity-to-location map:":
+        list_number = 7
+        continue
+    if list_number == 1:
+        seed_to_soil.append([int(x) for x in line.split()])
+    elif list_number == 2:
+        soil_to_fertilizer.append([int(x) for x in line.split()])
+    elif list_number == 3:
+        fertilizer_to_water.append([int(x) for x in line.split()])
+    elif list_number == 4:
+        water_to_light.append([int(x) for x in line.split()])
+    elif list_number == 5:
+        light_to_temperature.append([int(x) for x in line.split()])
+    elif list_number == 6:
+        temperature_to_humidity.append([int(x) for x in line.split()])
+    elif list_number == 7:
+        humidity_to_location.append([int(x) for x in line.split()])
+input_file.close()
+
+seed_to_soil = np.asarray(seed_to_soil)
+soil_to_fertilizer = np.asarray(soil_to_fertilizer)
+fertilizer_to_water = np.asarray(fertilizer_to_water)
+water_to_light = np.asarray(water_to_light)
+light_to_temperature = np.asarray(light_to_temperature)
+temperature_to_humidity = np.asarray(temperature_to_humidity)
+humidity_to_location = np.asarray(humidity_to_location)
+
+
+@njit
+def find_dest(num, map_list):
+    for m in map_list:
+        if m[1] <= num < m[1] + m[2]:
+            return num - m[1] + m[0]
+    return num
+
+
+@njit
+def find_min(seed, ra):
+    min_location = - 1
+    print(f"gestartet: Seed: {seed} Range: {ra}")
+    for s in range(seed, seed + ra):
+        soil = find_dest(s, seed_to_soil)
+        fertilizer = find_dest(soil, soil_to_fertilizer)
+        water = find_dest(fertilizer, fertilizer_to_water)
+        light = find_dest(water, water_to_light)
+        temperature = find_dest(light, light_to_temperature)
+        humidity = find_dest(temperature, temperature_to_humidity)
+        location = find_dest(humidity, humidity_to_location)
+        if min_location == -1:
+            min_location = location
+        elif location < min_location:
+            min_location = location
+    print(f"beendet.. Seed: {seed} Range: {ra} MinLocation: {min_location}")
+    return min_location
+
+
+if __name__ == '__main__':
+    num_processes = 10
+
+    input_data = []
+    for i in range(0, len(seeds), 2):
+        input_data.append((seeds[i], seeds[i+1]))
+    # input_data manuell erstellt:
+    #    input_data = [(seeds[0], seeds[1]), (seeds[2], seeds[3]), (seeds[4], seeds[5]), (seeds[6], seeds[7]),
+    #                  (seeds[8], seeds[9]), (seeds[10], seeds[11]), (seeds[12], seeds[13]), (seeds[14], seeds[15]),
+    #                  (seeds[16], seeds[17]), (seeds[18], seeds[19])]
+
+    with Pool(processes=num_processes) as pool:
+        results = pool.starmap(find_min, input_data)
+    print(results)
+    print(f"kleinste Location: {min(results)}")
+    print(f"Script beendet! Benötigte Zeit in Sekunden: {int(time()-start)}")

05/05-2-multiprocessig-gpu-eric.py

@@ -0,0 +1,119 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+from multiprocessing import Pool
+from time import time
+
+import numpy as np
+from numba import jit
+
+seeds = []  # 0
+seed_to_soil = []  # 1
+soil_to_fertilizer = []  # 2
+fertilizer_to_water = []  # 3
+water_to_light = []  # 4
+light_to_temperature = []  # 5
+temperature_to_humidity = []  # 6
+humidity_to_location = []  # 7
+
+list_number = 0
+
+
+@jit(target_backend='cuda', nopython=True)
+def find_dest(num, map_list):
+    for m in map_list:
+        if m[1] <= num < m[1] + m[2]:
+            return num - m[1] + m[0]
+    return num
+
+
+# parse input
+input_file = open("input", "r")
+for line in input_file:
+    line = line.strip()
+    if line == "":
+        continue
+    if line.startswith('seeds: '):
+        seeds = [int(x) for x in line.replace('seeds: ', '').split()]
+    if line == "seed-to-soil map:":
+        list_number = 1
+        continue
+    if line == "soil-to-fertilizer map:":
+        list_number = 2
+        continue
+    if line == "fertilizer-to-water map:":
+        list_number = 3
+        continue
+    if line == "water-to-light map:":
+        list_number = 4
+        continue
+    if line == "light-to-temperature map:":
+        list_number = 5
+        continue
+    if line == "temperature-to-humidity map:":
+        list_number = 6
+        continue
+    if line == "humidity-to-location map:":
+        list_number = 7
+        continue
+    if list_number == 1:
+        seed_to_soil.append([int(x) for x in line.split()])
+    elif list_number == 2:
+        soil_to_fertilizer.append([int(x) for x in line.split()])
+    elif list_number == 3:
+        fertilizer_to_water.append([int(x) for x in line.split()])
+    elif list_number == 4:
+        water_to_light.append([int(x) for x in line.split()])
+    elif list_number == 5:
+        light_to_temperature.append([int(x) for x in line.split()])
+    elif list_number == 6:
+        temperature_to_humidity.append([int(x) for x in line.split()])
+    elif list_number == 7:
+        humidity_to_location.append([int(x) for x in line.split()])
+input_file.close()
+
+seeds = np.array(seeds)
+seed_to_soil = np.array(seed_to_soil)
+soil_to_fertilizer = np.array(soil_to_fertilizer)
+fertilizer_to_water = np.array(fertilizer_to_water)
+water_to_light = np.array(water_to_light)
+light_to_temperature = np.array(light_to_temperature)
+temperature_to_humidity = np.array(temperature_to_humidity)
+humidity_to_location = np.array(humidity_to_location)
+
+
+@jit(target_backend='cuda', nopython=True)
+def find_min(seed, ra):
+    min_location = - 1
+    print(f"gestartet: Seed: {seed} Range: {ra}")
+    for s in range(seed, seed + ra):
+        soil = find_dest(s, seed_to_soil)
+        fertilizer = find_dest(soil, soil_to_fertilizer)
+        water = find_dest(fertilizer, fertilizer_to_water)
+        light = find_dest(water, water_to_light)
+        temperature = find_dest(light, light_to_temperature)
+        humidity = find_dest(temperature, temperature_to_humidity)
+        location = find_dest(humidity, humidity_to_location)
+        if min_location == -1:
+            min_location = location
+        elif location < min_location:
+            min_location = location
+    print(f"beendet.. Seed: {seed} Range: {ra} MinLocation: {min_location}")
+    return min_location
+
+
+if __name__ == '__main__':
+    num_processes = 10
+
+    input_data = []
+    for i in range(0, len(seeds), 2):
+        input_data.append((seeds[i], seeds[i + 1]))
+    input_data = np.array(input_data)
+
+    start = time()
+    with Pool(processes=num_processes) as pool:
+        results = pool.starmap(find_min, input_data)
+    print(results)
+    print(f"kleinste Location: {min(results)}")
+
+    print(f"Benötigte Zeit: {round(time() - start)}s")
+    input("")