diff --git a/network/h_dynamic_cnn_gpu_cpp/HDynamicCNNGPU.cu b/network/h_dynamic_cnn_gpu_cpp/HDynamicCNNGPU.cu
deleted file mode 100644
index 4237406..0000000
--- a/network/h_dynamic_cnn_gpu_cpp/HDynamicCNNGPU.cu
+++ /dev/null
@@ -1,472 +0,0 @@
-#include "HDynamicCNNGPU.h"
-
-#include <omp.h>
-#include <stdio.h>
-#include <string.h>
-
-#include <algorithm>
-#include <cassert>
-#include <iostream>
-
-
-HDynamicCNNGPU::HDynamicCNNGPU()
-{
-
-};
-
-HDynamicCNNGPU::~HDynamicCNNGPU()
-{
-
-};
-
-void HDynamicCNNGPU::entrypoint(
-    int64_t h_pointer_addr,
-    int64_t h_dim_0,
-    int64_t h_dim_1,
-    int64_t h_dim_2,
-    int64_t h_dim_3,
-    int64_t epsilon_xy_pointer_addr,
-    int64_t epsilon_xy_dim_0,
-    int64_t epsilon_xy_dim_1,
-    int64_t epsilon_xy_dim_2,
-    int64_t epsilon_t_pointer_addr,
-    int64_t epsilon_t_dim_0,
-    int64_t weights_pointer_addr,
-    int64_t weights_dim_0,
-    int64_t weights_dim_1,
-    int64_t input_pointer_addr,
-    int64_t input_dim_0,
-    int64_t input_dim_1,
-    int64_t input_dim_2,
-    int64_t input_dim_3,
-    int64_t init_vector_pointer_addr,
-    int64_t init_vector_dim_0,
-    int64_t number_of_processes,
-    float forgetting_offset,
-    int64_t gpu_tuning_factor)
-{
-
-    size_t number_of_pattern = input_dim_0;
-
-    size_t h_dim = init_vector_dim_0;
-    float* h_init_ptr = (float*)init_vector_pointer_addr;
-    assert((h_init_ptr != nullptr));
-    assert((h_dim > 0));
-
-    float* h_pointer = (float*)h_pointer_addr;
-    assert((h_pointer != nullptr));
-    assert((h_dim_0 > 0));
-    assert((h_dim_1 > 0));
-    assert((h_dim_2 > 0));
-    assert((h_dim_3 > 0));
-
-    size_t h_dim_c0 = h_dim_1 * h_dim_2 * h_dim_3;
-    size_t h_dim_c1 = h_dim_2 * h_dim_3;
-    size_t h_dim_c2 = h_dim_3;
-
-    float* epsilon_xy_pointer = (float*)epsilon_xy_pointer_addr;
-    assert((epsilon_xy_pointer != nullptr));
-    assert((epsilon_xy_dim_0 > 0));
-    assert((epsilon_xy_dim_1 > 0));
-
-    size_t epsilon_xy_dim_c0 = epsilon_xy_dim_2 * epsilon_xy_dim_1;
-    size_t epsilon_xy_dim_c1 = epsilon_xy_dim_2;
-
-    float* epsilon_t_pointer = (float*)epsilon_t_pointer_addr;
-    assert((epsilon_t_pointer != nullptr));
-    assert((epsilon_t_dim_0 > 0));
-
-    float* weights_pointer = (float*)weights_pointer_addr;
-    assert((weights_pointer != nullptr));
-    assert((weights_dim_0 > 0));
-    assert((weights_dim_1 > 0));
-
-    size_t weights_dim_c0 = weights_dim_1;
-
-    int64_t* input_pointer = (int64_t*)input_pointer_addr;
-    assert((input_pointer != nullptr));
-    assert((input_dim_0 > 0));
-    assert((input_dim_1 > 0));
-    assert((input_dim_2 > 0));
-    assert((input_dim_3 > 0));
-
-    size_t input_dim_c0 = input_dim_1 * input_dim_2 * input_dim_3;
-    size_t input_dim_c1 = input_dim_2 * input_dim_3;
-    size_t input_dim_c2 = input_dim_3;
-
-    assert((h_dim == weights_dim_1));
-    size_t number_of_spikes = input_dim_1;
-    size_t dim_x = input_dim_2;
-    size_t dim_y = input_dim_3;
-
-    float forgetting_offset_local = forgetting_offset / static_cast<float>(h_dim);
-
-    // --------------------
-    assert ((number_of_processes <= 0));
-
-    gpu_update(
-        h_init_ptr,
-        h_pointer,
-        h_dim_c0,
-        h_dim_c1,
-        h_dim_c2,
-        h_dim,
-        epsilon_xy_pointer,
-        epsilon_xy_dim_c0,
-        epsilon_xy_dim_c1,
-        epsilon_t_pointer,
-        weights_pointer,
-        weights_dim_c0,
-        input_pointer,
-        input_dim_c0,
-        input_dim_c1,
-        input_dim_c2,
-        number_of_spikes,
-        dim_x,
-        dim_y,
-        forgetting_offset,
-        forgetting_offset_local,
-        number_of_pattern,
-        gpu_tuning_factor);
-
-    return;
-};
-
-__device__ void gpu_update_one_ip(
-    float* __restrict__ h_init_ptr,
-    float* __restrict__ h_pointer,
-    size_t h_dim_c1,
-    size_t h_dim,
-    float* __restrict__ weights_pointer,
-    size_t weights_dim_c0,
-    int64_t* input_pointer,
-    size_t input_dim_c1,
-    float* __restrict__ epsilon_xy_pointer,
-    size_t epsilon_xy_dim_c0,
-    float* __restrict__ epsilon_t_pointer,
-    size_t number_of_spikes,
-    float forgetting_offset,
-    float forgetting_offset_local,
-    float* __restrict__ h_temp,
-    float* __restrict__ h_subsegment
-)
-{
-
-    float h_temp_sum;
-    float temp_value;
-
-    float epsilon_subsegment;
-    float epsilon_scale = 1.0;
-
-    int64_t* spike;
-    float* w_ptr;
-
-    // float* h_temp = new float[h_dim];
-    // float* h_subsegment = new float[h_dim];
-
-    // Initialize the sub-segement
-    for (size_t counter = 0; counter < h_dim; counter++)
-    {
-        h_subsegment[counter] = h_init_ptr[counter];
-    }
-
-    for (size_t counter_spike = 0; counter_spike < number_of_spikes; counter_spike++)
-    {
-        if (epsilon_scale > 1E10)
-        {
-            temp_value = 1.0 / epsilon_scale;
-
-            for (size_t counter = 0; counter < h_dim; counter++)
-            {
-                h_subsegment[counter] *= temp_value;
-            }
-
-            epsilon_scale = 1.0;
-        }
-
-        spike = input_pointer + counter_spike * input_dim_c1;
-
-        if (*spike >= 0)
-        {
-            epsilon_subsegment =
-                epsilon_xy_pointer[*spike *epsilon_xy_dim_c0] * epsilon_t_pointer[counter_spike];
-
-            w_ptr = weights_pointer + *spike * weights_dim_c0;
-
-            for (size_t counter = 0; counter < h_dim; counter++)
-            {
-                h_temp[counter] = h_subsegment[counter] * w_ptr[counter];
-            }
-
-            h_temp_sum = 0.0;
-
-            for (size_t counter = 0; counter < h_dim; counter++)
-            {
-                h_temp_sum += h_temp[counter];
-            }
-
-            if (h_temp_sum > 1E-10)
-            {
-                temp_value = epsilon_scale * epsilon_subsegment / h_temp_sum;
-
-                for (size_t counter = 0; counter < h_dim; counter++)
-                {
-                    h_temp[counter] *= temp_value;
-                }
-
-                for (size_t counter = 0; counter < h_dim; counter++)
-                {
-                    h_subsegment[counter] += h_temp[counter];
-                }
-
-                if (forgetting_offset_local > 0.0)
-                {
-                    temp_value =
-                        epsilon_scale * epsilon_subsegment * forgetting_offset_local;
-
-                    for (size_t counter = 0; counter < h_dim; counter++)
-                    {
-                        h_subsegment[counter] += temp_value;
-                    }
-
-                    epsilon_scale *=
-                        1.0 + epsilon_subsegment * (1.0 + forgetting_offset);
-                }
-                else
-                {
-                    epsilon_scale *= 1.0 + epsilon_subsegment * 1.0;
-                }
-            }
-        }
-    }
-
-    temp_value = 1.0 / epsilon_scale;
-
-    for (size_t counter = 0; counter < h_dim; counter++)
-    {
-        h_pointer[counter * h_dim_c1] =
-            h_subsegment[counter] * temp_value;
-    }
-
-    // delete[] h_temp;
-    // delete[] h_subsegment;
-
-    return;
-};
-
-__global__ void kernel_spike_generation(
-    float* __restrict__ h_init_ptr,
-    float* __restrict__ h_pointer,
-    size_t h_dim_c0,
-    size_t h_dim_c1,
-    size_t h_dim_c2,
-    size_t h_dim,
-    float* __restrict__ weights_pointer,
-    size_t weights_dim_c0,
-    int64_t* __restrict__ input_pointer,
-    size_t input_dim_c0,
-    size_t input_dim_c1,
-    size_t input_dim_c2,
-    float* __restrict__ epsilon_xy_pointer,
-    size_t epsilon_xy_dim_c0,
-    size_t epsilon_xy_dim_c1,
-    float* __restrict__ epsilon_t_pointer,
-    size_t number_of_spikes,
-    float forgetting_offset,
-    float forgetting_offset_local,
-    size_t dim_x,
-    size_t dim_y,
-    size_t dim_xy,
-    size_t max_threadable_tasks,
-    float* __restrict__ temp_memory_a,
-    float* __restrict__ temp_memory_b
-)
-{
-
-    int idx = threadIdx.x + blockIdx.x * blockDim.x;
-
-    if (idx < max_threadable_tasks)
-    {
-        float* h_ptr;
-        float* epsilon_xy_ptr;
-        int64_t* input_ptr;
-
-        float* temp_memory_ptr_a = temp_memory_a + idx * h_dim;
-        float* temp_memory_ptr_b = temp_memory_b + idx * h_dim;
-
-        // int pattern_id = idx; 
-        int pattern_id = idx / dim_xy;
-        int position_xy = idx - (pattern_id * dim_xy);
-
-        // size_t position_x = blockIdx.y;
-        // size_t position_y = blockIdx.z;
-        size_t position_x = position_xy / dim_y;
-        size_t position_y = position_xy - (position_x * dim_y);
-
-        epsilon_xy_ptr = epsilon_xy_pointer +
-            position_x * epsilon_xy_dim_c1 + position_y;
-
-        h_ptr = h_pointer +
-            pattern_id * h_dim_c0 + position_x * h_dim_c2 + position_y;
-
-        input_ptr = input_pointer +
-            pattern_id * input_dim_c0 + position_x * input_dim_c2 + position_y;
-
-        gpu_update_one_ip(
-            h_init_ptr,
-            h_ptr,
-            h_dim_c1,
-            h_dim,
-            weights_pointer,
-            weights_dim_c0,
-            input_ptr,
-            input_dim_c1,
-            epsilon_xy_ptr,
-            epsilon_xy_dim_c0,
-            epsilon_t_pointer,
-            number_of_spikes,
-            forgetting_offset,
-            forgetting_offset_local,
-            temp_memory_ptr_a,
-            temp_memory_ptr_b
-        );
-
-    }
-
-};
-
-// Let's face it... We need a better way to paralelize it...
-void HDynamicCNNGPU::gpu_update(
-    float* h_init_ptr,
-    float* h_pointer,
-    size_t h_dim_c0,
-    size_t h_dim_c1,
-    size_t h_dim_c2,
-    size_t h_dim,
-    float* epsilon_xy_pointer,
-    size_t epsilon_xy_dim_c0,
-    size_t epsilon_xy_dim_c1,
-    float* epsilon_t_pointer,
-    float* weights_pointer,
-    size_t weights_dim_c0,
-    int64_t* input_pointer,
-    size_t input_dim_c0,
-    size_t input_dim_c1,
-    size_t input_dim_c2,
-    size_t number_of_spikes,
-    size_t dim_x,
-    size_t dim_y,
-    float forgetting_offset,
-    float forgetting_offset_local,
-    size_t number_of_pattern,
-    size_t gpu_tuning_factor)
-{
-
-    cudaError_t status;
-    assert((dim_x < 65535));
-    assert((dim_y < 65535));
-
-    // //////////////////////////////////////
-    // Calculate the distribution on the GPU
-    // //////////////////////////////////////
-
-    int min_grid_size;
-    int block_size;
-    int grid_size;
-
-    size_t dynamic_s_mem_size = 0;
-    size_t max_threadable_tasks = number_of_pattern * dim_x * dim_y;
-
-    // https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html?highlight=blocksize#occupancy-calculator
-    status = cudaOccupancyMaxPotentialBlockSize(&min_grid_size, &block_size,
-        (void*)kernel_spike_generation,
-        dynamic_s_mem_size, max_threadable_tasks);
-    assert((status == cudaSuccess));
-
-    // https://docs.nvidia.com/cuda/cuda-c-programming-guide/index.html#features-and-technical-specifications
-    // Maximum dimensionality of grid of thread blocks: 3
-    // Maximum x -dimension of a grid of thread blocks: (2^31)-1
-    // Maximum y- or z-dimension of a grid of thread blocks: 65535
-
-    // Reduce the automatic block size with our guess 
-    if ((gpu_tuning_factor > 0) && (gpu_tuning_factor < block_size))
-    {
-        block_size = int(gpu_tuning_factor);
-    }
-    // Round up according to array size
-    // (I will separate x and y into other grid dimentsions soon)
-    // grid_size = (number_of_pattern + block_size - 1) / block_size;
-    grid_size = (max_threadable_tasks + block_size - 1) / block_size;
-
-    float* temp_memory_a = nullptr;
-    status = cudaMalloc((void**)&temp_memory_a, h_dim * max_threadable_tasks * sizeof(float));
-    assert((status == cudaSuccess));
-
-    float* temp_memory_b = nullptr;
-    status = cudaMalloc((void**)&temp_memory_b, h_dim * max_threadable_tasks * sizeof(float));
-    assert((status == cudaSuccess));
-
-
-    //kernel_spike_generation<<<grid, block_size >>>(
-    kernel_spike_generation<<<grid_size, block_size >>>(
-        h_init_ptr,
-        h_pointer,
-        h_dim_c0,
-        h_dim_c1,
-        h_dim_c2,
-        h_dim,
-        weights_pointer,
-        weights_dim_c0,
-        input_pointer,
-        input_dim_c0,
-        input_dim_c1,
-        input_dim_c2,
-        epsilon_xy_pointer,
-        epsilon_xy_dim_c0,
-        epsilon_xy_dim_c1,
-        epsilon_t_pointer,
-        number_of_spikes,
-        forgetting_offset,
-        forgetting_offset_local,
-        dim_x,
-        dim_y,
-        (dim_x * dim_y),
-        //number_of_pattern
-        max_threadable_tasks,
-        temp_memory_a,
-        temp_memory_b
-        );
-
-    status = cudaDeviceSynchronize();
-    assert((status == cudaSuccess));
-
-    status = cudaFree(temp_memory_a);
-    assert((status == cudaSuccess));
-
-    status = cudaFree(temp_memory_b);
-    assert((status == cudaSuccess));
-
-    return;
-};
-
-
-void HDynamicCNNGPU::gpu_occupancy_export(
-    size_t dim_x,
-    size_t dim_y,
-    size_t number_of_pattern,
-    size_t h_dim,
-    int64_t setting_memory_addr,
-    size_t setting_dim_0,
-    size_t setting_dim_1)
-{
-    return;
-};
-
-void HDynamicCNNGPU::gpu_occupancy_import(
-    int64_t setting_memory_addr,
-    size_t setting_dim_0,
-    size_t setting_dim_1
-)
-{
-    return;
-};
\ No newline at end of file
diff --git a/network/h_dynamic_cnn_gpu_cpp/HDynamicCNNGPU.h b/network/h_dynamic_cnn_gpu_cpp/HDynamicCNNGPU.h
deleted file mode 100644
index 235bad4..0000000
--- a/network/h_dynamic_cnn_gpu_cpp/HDynamicCNNGPU.h
+++ /dev/null
@@ -1,84 +0,0 @@
-#ifndef HDYNAMICCNNGPU
-#define HDYNAMICCNNGPU
-
-#include <unistd.h>
-
-#include <cctype>
-#include <iostream>
-
-class HDynamicCNNGPU
-{
-public:
-    HDynamicCNNGPU();
-    ~HDynamicCNNGPU();
-
-    void entrypoint(
-        int64_t h_pointer_addr,
-        int64_t h_dim_0,
-        int64_t h_dim_1,
-        int64_t h_dim_2,
-        int64_t h_dim_3,
-        int64_t epsilon_xy_pointer_addr,
-        int64_t epsilon_xy_dim_0,
-        int64_t epsilon_xy_dim_1,
-        int64_t epsilon_xy_dim_2,
-        int64_t epsilon_t_pointer_addr,
-        int64_t epsilon_t_dim_0,
-        int64_t weights_pointer_addr,
-        int64_t weights_dim_0,
-        int64_t weights_dim_1,
-        int64_t input_pointer_addr,
-        int64_t input_dim_0,
-        int64_t input_dim_1,
-        int64_t input_dim_2,
-        int64_t input_dim_3,
-        int64_t init_vector_pointer_addr,
-        int64_t init_vector_dim_0,
-        int64_t number_of_processes,
-        float forgetting_offset,
-        int64_t gpu_tuning_factor);
-
-    void gpu_occupancy_export(
-        size_t dim_x,
-        size_t dim_y,
-        size_t number_of_pattern,
-        size_t h_dim,
-        int64_t setting_memory_addr,
-        size_t setting_dim_0,
-        size_t setting_dim_1);
-
-    void gpu_occupancy_import(
-        int64_t setting_memory_addr,
-        size_t setting_dim_0,
-        size_t setting_dim_1);
-
-private:
-
-    void gpu_update(
-        float* h_init_ptr,
-        float* h_pointer,
-        size_t h_dim_c0,
-        size_t h_dim_c1,
-        size_t h_dim_c2,
-        size_t h_dim,
-        float* epsilon_xy_pointer,
-        size_t epsilon_xy_dim_c0,
-        size_t epsilon_xy_dim_c1,
-        float* epsilon_t_pointer,
-        float* weights_pointer,
-        size_t weights_dim_c0,
-        int64_t* input_pointer,
-        size_t input_dim_c0,
-        size_t input_dim_c1,
-        size_t input_dim_c2,
-        size_t number_of_spikes,
-        size_t dim_x,
-        size_t dim_y,
-        float forgetting_offset,
-        float forgetting_offset_local,
-        size_t number_of_pattern,
-        size_t gpu_tuning_factor);
-
-};
-
-#endif /* HDYNAMICCNNGPU */
diff --git a/network/h_dynamic_cnn_gpu_cpp/Makefile b/network/h_dynamic_cnn_gpu_cpp/Makefile
deleted file mode 100644
index acdc799..0000000
--- a/network/h_dynamic_cnn_gpu_cpp/Makefile
+++ /dev/null
@@ -1,33 +0,0 @@
-include ../.env
-export
-
-name = HDynamicCNN
-type = GPU
-
-PYPOSTFIX := $(shell $(PYBIN)python3-config --extension-suffix)
-PYBIND11INCLUDE := $(shell $(PYBIN)python3 -m pybind11 --includes)
-PARAMETERS_O = $(PARAMETERS_O_GPU) $(PYBIND11INCLUDE) 
-PARAMETERS_Linker = $(PARAMETERS_Linker_GPU)
-
-so_file = Py$(name)$(type)$(PYPOSTFIX)
-pyi_file = Py$(name)$(type).pyi
-all: ../$(so_file)
-
-$(O_DIRS)$(name)$(type).o: $(name)$(type).h $(name)$(type).cu
-	mkdir -p $(O_DIRS) 
-	$(NVCC) $(PARAMETERS_O) -c $(name)$(type).cu -o $(O_DIRS)$(name)$(type).o
-
-$(O_DIRS)Py$(name)$(type).o: $(name)$(type).h Py$(name)$(type).cpp 
-	mkdir -p $(O_DIRS)
-	$(NVCC) $(PARAMETERS_O) -c Py$(name)$(type).cpp -o $(O_DIRS)Py$(name)$(type).o
-
-../$(so_file): $(O_DIRS)$(name)$(type).o $(O_DIRS)Py$(name)$(type).o
-	$(NVCC) $(PARAMETERS_Linker) -o ../$(so_file) $(O_DIRS)$(name)$(type).o $(O_DIRS)Py$(name)$(type).o
-
-
-#######################
-clean:
-	rm -rf $(O_DIRS)
-	rm -f ../$(so_file)
-	rm -f ../$(pyi_file)
-
diff --git a/network/h_dynamic_cnn_gpu_cpp/PyHDynamicCNNGPU.cpp b/network/h_dynamic_cnn_gpu_cpp/PyHDynamicCNNGPU.cpp
deleted file mode 100644
index 999b6a6..0000000
--- a/network/h_dynamic_cnn_gpu_cpp/PyHDynamicCNNGPU.cpp
+++ /dev/null
@@ -1,18 +0,0 @@
-#include <pybind11/pybind11.h>
-
-#include "HDynamicCNNGPU.h"
-
-namespace py = pybind11;
-
-PYBIND11_MODULE(PyHDynamicCNNGPU, m)
-{
-    m.doc() = "HDynamicCNNGPU Module";
-    py::class_<HDynamicCNNGPU>(m, "HDynamicCNNGPU")
-        .def(py::init<>())
-        .def("gpu_occupancy_export",
-            &HDynamicCNNGPU::gpu_occupancy_export)
-        .def("gpu_occupancy_import",
-            &HDynamicCNNGPU::gpu_occupancy_import)
-        .def("update",
-            &HDynamicCNNGPU::entrypoint);
-}
\ No newline at end of file