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diff --git a/sem4/hpp/m10/template.py b/sem4/hpp/m10/template.py
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+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+# A short template to test small kernels.
+# 
+
+import numpy as np
+import pyopencl as cl
+
+VEC_SIZE = 50000
+
+# Create the context (containing platform and device information) and command queue.
+context = cl.create_some_context()
+cmd_queue = cl.CommandQueue(context)
+
+# Create the host side data and a empty array to hold the result.
+a_host = np.random.rand(VEC_SIZE).astype(np.float32)
+b_host = np.random.rand(VEC_SIZE).astype(np.float32)
+result_host = np.empty_like(a_host)
+
+# Create a device side read-only memory buffer and copy the data from "hostbuf" into it.
+# Create as many 
+# You can find the other possible mem_flags values at
+# https://www.khronos.org/registry/OpenCL/sdk/1.2/docs/man/xhtml/clCreateBuffer.html
+mf = cl.mem_flags
+a_device = cl.Buffer(context, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=a_host)
+b_device = cl.Buffer(context, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=b_host)
+result_device = cl.Buffer(context, mf.WRITE_ONLY, a_host.nbytes)
+
+# Source of the kernel itself.
+kernel_source = """
+__kernel void sum(
+    __global const float *a_device, 
+    __global const float *b_device, 
+    __global       float *result_device)
+{
+  int gid = get_global_id(0);
+  result_device[gid] = a_device[gid] * b_device[gid];
+}
+"""
+
+# If you want to keep the kernel in a seperate file uncomment this line and adjust the filename
+#kernel_source = open("kernel.cl").read()
+
+# Create a new program from the kernel and build the source.
+prog = cl.Program(context, kernel_source).build()
+
+# Execute the "sum" kernel in the program. Parameters are:
+# 
+#        Command queue         Work group size   Kernel param 1
+#            ↓   Global grid size   ↓   Kernel param 0  ↓  Kernel param 2
+#            ↓           ↓          ↓       ↓           ↓        ↓
+prog.sum(cmd_queue, a_host.shape, None, a_device, b_device, result_device)
+
+# Copy the result back from device to host.
+cl.enqueue_copy(cmd_queue, result_host, result_device)
+
+# Check the results in the host array with Numpy.
+print("All elements close?", np.allclose(result_host, (a_host * b_host)))