Minor changes in matrix_matrix notebook

notebooks/matrix_matrix.ipynb

@@ -255,6 +255,19 @@
     "<b>Question:</b>  Which is the complexity (number of operations) of the serial algorithm? Assume that all matrices are $N$-by-$N$ matrices.    \n",
     "</div>\n",
     "\n",
+    "```julia\n",
+    "for j in 1:N\n",
+    "    for i in 1:N\n",
+    "        Cij = z\n",
+    "        for k in 1:N\n",
+    "            @inbounds Cij += A[i,k]*B[k,j]\n",
+    "        end\n",
+    "        C[i,j] = Cij\n",
+    "    end\n",
+    "end\n",
+    "```\n",
+    "\n",
+    "\n",
     "    a) O(1)\n",
     "    b) O(N)\n",
     "    c) O(N²)\n",
@@ -538,7 +551,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "dac6a50b",
+   "id": "501d4008",
    "metadata": {},
    "source": [
     "### Communication overhead\n",
@@ -553,8 +566,25 @@
     "\n",
     "<div class=\"alert alert-block alert-success\">\n",
     "<b>Question:</b>  How many scalars are communicated from and to a worker?  Assume that matrices A, B, and C are N by N matrices.\n",
+    "</div>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "45f44171",
+   "metadata": {},
+   "source": [
+    " <div>\n",
+    "<img src=\"data:image/png;base64,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 truncated
     "</div>\n",
-    "\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "dac6a50b",
+   "metadata": {},
+   "source": [
     "    a) O(1)\n",
     "    b) O(N)\n",
     "    c) O(N²)\n",
@@ -796,7 +826,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e2c6f60a",
+   "id": "2b1e3b24",
    "metadata": {},
    "source": [
     "### Complexity\n",
@@ -809,8 +839,25 @@
     "\n",
     "<div class=\"alert alert-block alert-success\">\n",
     "<b>Question:</b>  Which is the complexity of the communication and computations done by a worker in algorithm 2?\n",
-    "</div>\n",
+    "</div>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "77808863",
+   "metadata": {},
+   "source": [
     "\n",
+    "<div>\n",
+    "<img src=\"data:image/png;base64,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 truncated
+    "</div>\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e2c6f60a",
+   "metadata": {},
+   "source": [
     "    a) O(N) communication and O(N^2) computation\n",
     "    b) O(N^2) communication and O(N^2) computation\n",
     "    c) O(N^3) communication and O(N^3) computation\n",
@@ -1020,8 +1067,6 @@
     "    @assert size(B,1) == l\n",
     "    @assert mod(m,nworkers()) == 0\n",
     "    # Implement here\n",
-    "    \n",
-    "    C\n",
     "end"
    ]
   },
@@ -1066,7 +1111,7 @@
    "outputs": [],
    "source": [
     "P = nworkers()\n",
-    "load = 100\n",
+    "load = 50 # try with 50, 100, and 200\n",
     "N = load*P\n",
     "A = rand(N,N)\n",
     "B = rand(N,N)\n",