remove unused modules

epgpu.cu

@@ -291,8 +291,8 @@ __device__ void DAB_oldal(int v, int w, const vec3& C, const vec3& D, char* egys
     }
     }
 }
 }
 
 
-__global__ void gpu_egyensulyi(int v, int w, double* Cx_arr, double* Cy_arr, 
-                double* Dx_arr, double* Dy_arr, double* Dz_arr, int size_C, int size_D, int lcm, char* egysulyi_mtx) {
+__global__ void gpu_egyensulyi(int v, int w, const double* Cx_arr, const  double* Cy_arr, 
+               const double* Dx_arr, const double* Dy_arr, const double* Dz_arr, int size_C, int size_D, int lcm, char* egysulyi_mtx) {
     int pos = blockDim.x * blockIdx.x + threadIdx.x;
     int pos = blockDim.x * blockIdx.x + threadIdx.x;
     if (pos >= size_C*size_D)
     if (pos >= size_C*size_D)
         return;
         return;

genax.py

-import cupy as cp, matplotlib.pyplot as plt
+import cupy as cp
 from numba import cuda
 from numba import cuda
 from utils import expSpace
 from utils import expSpace
 from mpi import size, rank
 from mpi import size, rank
 
 
-def gen_angels_to_pick(n, plot = False):
+def gen_angels_to_pick(n):
     if n % 2 == 0:
     if n % 2 == 0:
         raise "n%2==0"
         raise "n%2==0"
     N = int((n + 3) / 2)
     N = int((n + 3) / 2)
@@ -14,11 +14,6 @@ def gen_angels_to_pick(n, plot = False):
     anglestopick = cp.concatenate((X1, X3), axis=None)
     anglestopick = cp.concatenate((X1, X3), axis=None)
     anglestopick = cp.unique(anglestopick) # Vigyázni vele!
     anglestopick = cp.unique(anglestopick) # Vigyázni vele!
     anglestopick = anglestopick[1:-1]
     anglestopick = anglestopick[1:-1]
-
-    if plot:
-        Y = cp.zeros(n)
-        plt.plot(anglestopick, Y, '|')
-        plt.show()
     
     
     return anglestopick
     return anglestopick
 
 

tetrarun.py

@@ -37,12 +37,14 @@ def main(argv):
       elif opt in ("-m", "--mpi"):
       elif opt in ("-m", "--mpi"):
          mpi = True
          mpi = True
 
 
-   space = gen_angels_to_pick(n, PLOT)
+   space = gen_angels_to_pick(n)
 
 
    Cx, Cy = angles_alap(space)
    Cx, Cy = angles_alap(space)
 
 
    Dx, Dy, Dz = angles_ratet(space, mpi)
    Dx, Dy, Dz = angles_ratet(space, mpi)
 
 
+   del space
+
    res = start_kernel(Cx, Cy, Dx, Dy, Dz, v, w)
    res = start_kernel(Cx, Cy, Dx, Dy, Dz, v, w)
 
 
    Cx_cpu = np.zeros(Cx.size, dtype=np.float64)
    Cx_cpu = np.zeros(Cx.size, dtype=np.float64)

utils.py

 import cupy as cp
 import cupy as cp
-from functools import wraps
 import time
 import time
 import numpy as np
 import numpy as np
 from mpi import size, rank
 from mpi import size, rank
@@ -12,17 +11,6 @@ ep_pontok_module = cp.RawModule(code=code, options=('--std=c++11',), name_expres
 exact_one_cuda = ep_pontok_module.get_function(kers[0])
 exact_one_cuda = ep_pontok_module.get_function(kers[0])
 filter_cuda = ep_pontok_module.get_function(kers[1])
 filter_cuda = ep_pontok_module.get_function(kers[1])
 
 
-def timeit(func):
-    @wraps(func)
-    def timeit_wrapper(*args, **kwargs):
-        start_time = time.perf_counter()
-        result = func(*args, **kwargs)
-        end_time = time.perf_counter()
-        total_time = end_time - start_time
-        print(f'Function {func.__name__}{args} {kwargs} Took {total_time:.4f} seconds')
-        return result
-    return timeit_wrapper
-
 def expSpace(min, max, N, exponentialliness = 20.0):
 def expSpace(min, max, N, exponentialliness = 20.0):
     LinVec = cp.linspace(0, cp.log10(exponentialliness+1, dtype=cp.float64),N, dtype=cp.float64)
     LinVec = cp.linspace(0, cp.log10(exponentialliness+1, dtype=cp.float64),N, dtype=cp.float64)
     return (max-min)/exponentialliness * (10.0**LinVec - 1) + min
     return (max-min)/exponentialliness * (10.0**LinVec - 1) + min