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    "## 5.4 Control Instructions\n",
    "\n",
    "Control instructions change the sequence of the instructions that are executed. If\n",
    "there were no control instructions, the next instruction fetched after the current\n",
    "instruction finishes would be the instruction located in the next sequential memory\n",
    "location. As you know, this is because the PC is incremented before\n",
    "executing an instruction. We will see momentarily that it is often useful to be able to\n",
    "break that sequence.\n",
    "\n",
    "The LC-3 has five opcodes that enable this sequential flow to be broken: \n",
    "\n",
    "* conditional branch\n",
    "* unconditional jump\n",
    "* subroutine (sometimes called function) call\n",
    "* TRAP and return from interrupt. \n",
    "\n",
    "In this section, we will deal almost exclusively\n",
    "with the most common control instruction, the conditional branch. We will also\n",
    "introduce the unconditional jump and the TRAP instruction. The TRAP instruction\n",
    "is particularly useful because, among other things, it allows a programmer\n",
    "to get information into and out of the computer without fully understanding the\n",
    "intricacies of the input and output devices. However, most of the discussion of the\n",
    "TRAP instruction and all of the discussion of the subroutine call and the return\n",
    "from interrupt we will leave for Chapters 9 and 10. \n",
    "\n",
    "### 5.4.1 Conditional Branches\n",
    "\n",
    "The format of the conditional branch instruction (opcode = 0000) is as follows:\n",
    "\n",
    "Opcode | [11:9] | [8:0]\n",
    "-------| ------ | -----\n",
    "0000   | NZP    | VVVVVVVVV\n",
    "\n",
    "Bits [11], [10], and [9] correspond to the three condition codes discussed in\n",
    "Section 5.1.7. Recall that in the LC-3, all instructions that write values into the\n",
    "general purpose registers set the three condition codes (i.e., the single-bit registers\n",
    "N, Z, P) in accordance with whether the value written is negative, zero, or positive.\n",
    "These instructions are ADD, AND, NOT, LD, LDI, LDR, and LEA. \n",
    "\n",
    "The next instruction will be at the address that is computed by adding the\n",
    "incremented PC to the 16-bit value formed by sign-extending bits [8:0] of the\n",
    "BR instruction. \n",
    "\n",
    "Consider this example: the last value loaded into a general purpose register was 0,\n",
    "and the current instruction (located at x4027) is as shown here:\n",
    "\n",
    "```\n",
    "x4026: ...\n",
    "x4027: 0000 010 011011001 \n",
    "x4028: ...\n",
    "```\n",
    "We see that this is a BR opcode (0000) and if the last value loaded into a GPR is a Z (zero), then we will BRANCH to the PC + 011011001. \n",
    "\n",
    "```\n",
    "0 1101 1001 = x0D9 = D * 16 + 9 = 13 * 16 + 9 = 217\n",
    "```\n",
    "\n",
    "```\n",
    "  11\n",
    "x4028\n",
    "x00D9\n",
    "------\n",
    "x4101\n",
    "```\n",
    "\n",
    "So, this would load the PC with x4101, and the next instruction executed would be the\n",
    "one at x4101, rather than the instruction at x4028. \n",
    "\n",
    "What does each of these do?\n",
    "\n",
    "Q1:\n",
    "```\n",
    "0000 111 000000000 \n",
    "```\n",
    "\n",
    "Q2:\n",
    "```\n",
    "0000 111 000000001 \n",
    "```\n",
    "\n",
    "Q3:\n",
    "```\n",
    "0000 111 111111111\n",
    "```\n",
    "\n",
    "Q4:\n",
    "```\n",
    "0000 000 100101101\n",
    "```"
   ]
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Algorithm\n",
    "\n",
    "Suppose we know that the 12 locations x3100 to x310B contain integers, and we wish to compute the sum of these 12 integers. \n",
    "\n",
    "![Screen%20Shot%202017-09-27%20at%208.31.09%20AM.png](attachment:Screen%20Shot%202017-09-27%20at%208.31.09%20AM.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First, as in all algorithms, we must initialize our variables. That is, we must\n",
    "set up the initial values of the variables that the computer will use in executing the\n",
    "program that solves the problem. There are three such variables: the address of\n",
    "the next integer to be added (assigned to R1), the running sum (assigned to R3),\n",
    "and the number of integers left to be added (assigned to R2). The three variables\n",
    "are initialized as follows: The address of the first integer to be added is put in R1.\n",
    "R3, which will keep track of the running sum, is initialized to 0. R2, which will\n",
    "keep track of the number of integers left to be added, is initialized to 12. Then the\n",
    "process of adding begins.\n",
    "\n",
    "The program repeats the process of loading into R4 one of the 12 integers,\n",
    "and adding it to R3. Each time we perform the ADD, we increment R1 so it will\n",
    "point to (i.e., contain the address of) the next number to be added and decrement\n",
    "R2 so we will know how many numbers still need to be added. When R2 becomes\n",
    "zero, the Z condition code is set, and we can detect that we are done. \n",
    "\n",
    "First, let's put the data into the correct places in memory:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Assembled! Use %dis or %dump to examine; use %exe to run.\n"
     ]
    }
   ],
   "source": [
    ".ORIG x3100\n",
    "0000 0000 0000 0000 ;; x3100\n",
    "0000 0000 0000 0000 ;; x3101\n",
    "0000 0000 0000 0000 ;; x3102\n",
    "0000 0000 0000 0000 ;; x3103\n",
    "0000 0000 0000 0000 ;; x3104\n",
    "0000 0000 0000 0000 ;; x3105\n",
    "0000 0000 0000 0000 ;; x3106\n",
    "0000 0000 0000 0000 ;; x3107\n",
    "0000 0000 0000 0000 ;; x3108\n",
    "0000 0000 0000 0000 ;; x3109\n",
    "0000 0000 0000 0000 ;; x310A\n",
    "0000 0000 0000 0000 ;; x310B\n",
    ".END"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, we convert the above algorithm into machine code.\n",
    "\n",
    "The details of the program execution are as follows: The program starts with\n",
    "PC = x3000. \n",
    "\n",
    "```\n",
    "x3000: 1110 001 0 1111 1111  \n",
    "x3001: 0101 011 011 1 00000  \n",
    "x3002: 0101 010 010 1 00000  \n",
    "x3003: 0001 010 010 1 01100  \n",
    "x3004: 0000 010 000000101    \n",
    "x3005: 0110 100 001 000000   \n",
    "x3006: 0001 011 011 000100   \n",
    "x3007: 0001 001 001100001    \n",
    "x3008: 0001 010 010111111    \n",
    "x3009: 0000 111 111111010    \n",
    "x300A: 1111 0000 00100101    \n",
    "```\n",
    "\n",
    "The first instruction (at location x3000) loads R1 with the address\n",
    "x3100. (The incremented PC is x3001; the sign-extended PCoffset is xOOFF.)\n",
    "\n",
    "The instruction at x3001 clears R3. R3 will keep track of the running sum, so\n",
    "it must start off with the value 0. As we said previously, this is called initializing\n",
    "the SUM to zero.\n",
    "\n",
    "The instructions at x3002 and x3003 set the value of R2 to 12, the number of\n",
    "integers to be added. R2 will keep track of how many numbers have already been\n",
    "added. This will be done (by the instruction contained in x3008) by decrementing\n",
    "R2 after each addition takes place. \n",
    "\n",
    "The instruction at x3004 is a conditional branch instruction. Note that bit [10]\n",
    "is a 1. That means that the Z condition code will be examined. If it is set, we know \n",
    "R2 must have just been decremented to 0. That means there are no more numbers\n",
    "to be added and we are done. If it is clear, we know we still have work to do and\n",
    "we continue.\n",
    "\n",
    "The instruction at x3005 loads the contents of x3100 (i.e., the first integer)\n",
    "into R4, and the instruction at x3006 adds it to R3.\n",
    "\n",
    "The instructions at x3007 and x3008 perform the necessary bookkeeping.\n",
    "The instruction at x3007 increments Rl, so Rl will point to the next location in\n",
    "memory containing an integer to be added (in this case, x3101). The instruction\n",
    "at x3008 decrements R2, which is keeping track of the number of integers still to\n",
    "be added, as we have already explained, and sets the N, Z, and P condition codes.\n",
    "The instruction at x3009 is an unconditional branch, since bits [11:9] are all 1.\n",
    "It loads the PC with x3004. It also does not affect the condition codes, so the next\n",
    "instruction to be executed (the conditional branch at x3004) will be based on the\n",
    "instruction executed at x3008. \n",
    "\n",
    "This is worth saying again. The conditional branch instruction at x3004 follows\n",
    "the instruction at x3009, which does not affect condition codes, which in\n",
    "turn follows the instruction at x3008. Thus, the conditional branch instruction at\n",
    "x3004 will be based on the condition codes set by the instruction at x3008. The\n",
    "instruction at x3008 sets the condition codes depending on the value produced\n",
    "by decrementing R2. As long as there are still integers to be added, the ADD\n",
    "instruction at x3008 will produce a value greater than zero and therefore clear\n",
    "the Z condition code. The conditional branch instruction at x3004 examines the\n",
    "Z condition code. As long as Z is clear, the PC will not be affected, and the next\n",
    "instruction cycle will start with an instruction fetch from x3005."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Assembled! Use %dis or %dump to examine; use %exe to run.\n"
     ]
    }
   ],
   "source": [
    ".ORIG x3000\n",
    "1110 001 0 1111 1111  ;; R1 <- 3100   , LEA DST PCOFFSET9\n",
    "0101 011 011 1 00000  ;; R3 <- 0      , AND DST SRC #0\n",
    "0101 010 010 1 00000  ;; R2 <- 0      , AND DST SRC #0\n",
    "0001 010 010 1 01100  ;; R2 <- 12     , ADD DST SRC #12 \n",
    "0000 010 000000101    ;; BRz x300A    , BRz to HALT 5 below PC + 1 if zero\n",
    "0110 100 001 000000   ;; R4 <- M[R1]  , LDR DST BAS OFFSET6 \n",
    "0001 011 011 0 00 100 ;; R3 <- R3+R4  , ADD R3 <= R3 + R4\n",
    "0001 001 001 1 00001  ;; R1 <- R1 + 1 , ADD R1 <= R1 + 1\n",
    "0001 010 010 1 11111  ;; R2 <- R2 - 1 , ADD R2 <= R2 + -1\n",
    "0000 111 111111010    ;; BRnzp x3004  , BRnzp PC+1=x300A + -6, GOTO test\n",
    "1111 0000 00100101    ;; HALT\n",
    ".END"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The conditional branch instruction causes the execution sequence to follow:\n",
    "x3000, x3001, x3002, x3003, x3004, x3005, x3006, x3007, x3008, x3009, x3004,\n",
    "x3005, x3006, x3007, x3008, x3009, x3004, x3005, and so on until the value in R2\n",
    "becomes 0. The next time the conditional branch instruction at x3004 is executed,\n",
    "the PC is loaded with x300A, and the program continues at x300A with its next\n",
    "activity. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, it is worth noting that we could have written a program to add these\n",
    "12 integers without any control instructions. We still would have needed the LEA \n",
    "instruction in x3000 to initialize Rl. We would not have needed the instruction\n",
    "at x3001 to initialize the running sum, nor the instructions at x3002, and x3003\n",
    "to initialize the number of integers left to be added. We could have loaded the\n",
    "contents of x3100 directly into R3, and then repeatedly (by incrementing Rl,\n",
    "loading the next integer into R4, and adding R4 to the running sum in R3) added\n",
    "the remaining 11 integers. After the addition of the twelfth integer, we would go\n",
    "on to the next task, as does the example of Figure 5.13 with the branch instruction\n",
    "in x3004.\n",
    "\n",
    "Unfortunately, instead of a 10-instruction program, we would have had a 35-\n",
    "instruction program. Moreover, if we had wished to add 100 integers without any\n",
    "control instructions instead of 12, we would have had a 299-instruction program\n",
    "instead of 10. The control instructions in the example of Figure 5.13 permit the\n",
    "reuse of sequences of code by breaking the sequential instruction execution flow. \n",
    "\n",
    "For Monday:\n",
    "\n",
    "* 5.4.3 Two Methods for Loop Control \n",
    "* 5.4.4 Example: Adding a Column of Numbers Using a Sentinel \n",
    "* Run the example"
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