The purpose of this assignment is to help you learn about computer architecture, assembly language programming, and testing strategies. It also will give you the opportunity to learn more about the GNU/Linux programming tools, especially bash, emacs, gcc, gdb, and operf.
The assignment consists of two parts, each of which has subparts. We encourage you to complete Part 1 by the end of the first week of the assignment period.
Students from past semesters reported taking, on average, 22.5 hours to complete this assignment.
Part 2f, as defined below, is the "extra challenge" part of this assignment. While doing the "extra challenge" part of the assignment, you are bound to observe the course policies regarding assignment conduct as given in the course Policies web page, plus one additional policy: you may not use any "human" sources of information. That is, you may not consult with the course's staff members, the lab teaching assistants, other current students via Piazza, or any other people while working on the "extra challenge" part of an assignment, except for clarification of requirements.
The extra challenge part is worth 11 percent of this assignment. So if you don't do any of the "extra challenge" part and all other parts of your assignment solution are perfect and submitted on time, then your grade for the assignment will be 89 percent.
Develop on CourseLab. Use emacs to create source code. Use gdb to debug.
The CourseLab /u/cos217/Assignment4 directory contains files that you will find useful. Subsequent parts of this document describe them. Create a project directory, and copy all files from the /u/cos217/Assignment4 directory to your project directory.
Then complete the parts of the assignment given below, in the order of their appearance.
Do not use a C compiler to produce any of your assembly language code. Doing so would be considered academically dishonest. Instead produce your assembly language code manually.
We encourage you to develop "flattened" C code (as described in lectures and precepts) to bridge the gap between the given "normal" C code and your assembly language code. Using flattened C code as a bridge can eliminate logic errors from your assembly language code, leaving only the possibility of translation errors.
We also encourage you to use your flattened C code as comments in your assembly language code. Such comments can clarify your assembly language code substantially.
The Linux operating system has a command named wc (word count). In its simplest form, wc reads characters from stdin until end-of-file, and writes to stdout a count of how many lines, words, and characters it has read. A word is a sequence of characters that is delimited by one or more white space characters.
Consider some examples. In the following, a space is shown as s and a newline character as n.
If the file named proverb contains these characters:
Learningsissan treasureswhichn accompaniessitsn ownerseverywhere.n --sChinesesproverbn
then the command:
$ wc < proverb
writes this line to stdout:
5 12 82
If the file proverb2 contains these characters:
Learningsissan treasureswhichn accompaniessitsn ownerseverywhere.n --sssChinesesproverb
(note that the last "line" does not end with a newline character) then the command:
$ wc < proverb2
writes this line to stdout:
4 12 83
The given mywc.c file contains a C program that implements the subset of the wc command described above. Translate that program into assembly language, thus creating a file named mywc.s. Your mywc.s program must be an accurate translation of mywc.c. In particular, note that the given mywc.c program uses global variables, and so your mywc.s must use global variables too. That is, your mywc.s program must store data in the DATA and/or BSS sections. Your assembly language program must behave exactly the same (i.e. must write exactly the same characters to stdout) as the given C program does.
Compose data files that, when read by your mywc.s program, perform boundary tests, statement tests, and stress tests of that program. Name each test file such that its prefix is mywc and its suffix is .txt. The command ls mywc*.txt must display the names of all test files, and only those files.
Note that the logic implemented by your mywc.s program must be identical to the logic implemented by the given mywc.c program. So, for the sake of simplicity, let's assume that any test file that boundary/statement/stress tests mywc.c also boundary/statement/stress tests mywc.s.
Describe your test files in your readme file. Your descriptions must have this structure:
Boundary tests:
mywcXXX.txt: Description of the characteristics of that file, and how it tests boundary conditions of the mywc.c and mywc.s programs.
mywcYYY.txt: Description of the characteristics of that file, and how it tests boundary conditions of the mywc.c and mywc.s programs.
...
Statement tests:
mywcXXX.txt: Description of the characteristics of that file, and which lines of the mywc.c and mywc.s programs it causes the computer to execute.
mywcYYY.txt: Description of the characteristics of that file, and which lines of the mywc.c and mywc.s programs it causes the computer to execute.
...
Your description of each test file must be of the form "This file contains such-and-such characteristics, and so causes the computer to execute lines x, y, ..., and z of the given mywc.c" (where x, y, ..., and z are line numbers). Collectively your statement test files should cause the computer to execute all lines of the given mywc.c file (and so, by assumption, all lines of your mywc.s file).
Stress tests:
mywcXXX.txt: Description of the characteristics of that file, and how it stress tests the mywc.c and mywc.s programs.
mywcYYY.txt: Description of the characteristics of that file, and how it stress tests the mywc.c and mywc.s programs.
...
In a more realistic context, your test files should contain non-ASCII character codes. However, in the context of this assignment, submit test files that contain character codes for only printable characters. Specifically, make sure your computer-generated test files contain only character codes (in hexadecimal) 09, 0A, and 20 through 7E. It would be difficult for your grader to examine files that contain other character codes.
You may submit as many test files as you want. However at most three of your test files may be large, and a large test file must contain no more than 50000 characters and no more than 1000 lines. It would be difficult for your grader to scroll through a test file that exceeds those limits.
To test your mywc.s program, make sure that it writes the same output as mywc.c does when given each your test files as input. The given testmywc and testmywcdiff are Bash shell scripts that automate your testing. Comments at the beginning of those files describe how to use them. After copying the scripts to your project directory, you may need to execute the commands chmod 700 testmywc and chmod 700 testmywcdiff to give them "executable" permissions.
Many programming environments contain modules to handle high-precision integer arithmetic. For example, the Java Development Kit (JDK) contains the BigDecimal and BigInteger classes.
The Fibonacci numbers are used often in computer science. See http://en.wikipedia.org/wiki/Fibonacci_numbers for some background information. Note in particular that Fibonacci numbers can be very large integers.
This part of the assignment asks you to use assembly language to compose a minimal but fast high-precision integer arithmetic module, and use it to compute large Fibonacci numbers.
BigInt Objects Using C CodeSuppose you must compute Fibonacci number 500000, that is, fib(500000)...
You are given a C program that computes Fibonacci numbers. It consists of two modules: a client and a BigInt ADT.
The client consists of the file fib.c. The client accepts an integer x as a command-line argument, where x must be a non-negative integer. The client computes and writes fib(x) to stdout as a hexadecimal number. Then it writes to stderr the amount of CPU time consumed while performing the computation. Finally the client performs some boundary condition and stress tests, writing the results to stdout. The client module delegates most of the work to BigInt objects.
The BigInt ADT performs high precision integer arithmetic. It is a minimal ADT; essentially it implements only an "add" operation. The BigInt ADT consists of four files:
bigint.h is the interface. Note that the ADT makes eight functions available to clients: BigInt_new, BigInt_free, BigInt_assignFromHexString, BigInt_largest, BigInt_random, BigInt_writeHex, BigInt_writeHexAbbrev, and BigInt_add.
bigint.c contains implementations of the BigInt_new, BigInt_free, BigInt_assignFromHexString, BigInt_largest, BigInt_random, BigInt_writeHex, and BigInt_writeHexAbbrev functions.
bigintadd.c contains an implementation of the BigInt_add function.
bigintprivate.h is a private header file — private in the sense that clients never use it. It allows code to be shared between the two implementation files, bigint.c and bigintadd.c.
Study the given code. Then build a fib program consisting of the files fib.c, bigint.c, and bigintadd.c, with no optimizations (that is, without the -D NDEBUG option and without the -O option, as described below). Run the program to compute fib(500000). In your readme file note the amount of CPU time consumed.
BigInt Objects Using C Code Built with Compiler OptimizationSuppose you decide that the amount of CPU time consumed is unacceptably large. You decide to command the compiler to optimize the code that it produces...
Build the fib program using optimization. Specifically, build with the -D NDEBUG option so the preprocessor disables the assert macro, and the -O (that's an upper case "oh") option so the compiler generates optimized code. Run the resulting program to compute fib(500000). In your readme file note the amount of CPU time consumed.
Suppose you decide that the amount of CPU time consumed still is too large. You decide to investigate by doing an operf analysis to determine which functions are consuming the most time...
Perform an operf analysis of the executable binary file from Part 2b. (Use an opreport command with the -l option and only that option.) Save the textual report in a file named performance. Don't delete the file; as described later in this document, you must submit that file.
BigInt Objects Using Assembly Language CodeSuppose, not surprisingly, your operf analysis shows that most CPU time is spent executing the BigInt_add function. In an attempt to gain speed, you decide to code the BigInt_add function manually in assembly language...
Manually translate the C code in the bigintadd.c file into assembly language, thus creating the file bigintadd.s. Do not translate the code in other files into assembly language.
Your assembly language code must store all parameters and local variables defined in the BigInt_larger and BigInt_add functions in memory, on the stack.
Note that assert is a parameterized macro, not a function. (See Section 14.3 of the King book for a description of parameterized macros.) So assembly language code cannot call assert. When translating bigintadd.c to assembly language, simply pretend that the calls of assert are not in the C code.
Use .equ directives to avoid "magic numbers." In particular, in bigintadd.s use .equ directives to give meaningful names to:
Enumerated constants, for example: .equ TRUE, 1.
Parameter stack offsets, for example: .equ OADDEND1, 48.
Local variable stack offsets, for example: .equ ULCARRY, 24.
Structure field offsets, for example: .equ LLENGTH, 0.
Build a fib program consisting of the files fib.c, bigint.c, and bigintadd.s using the -D NDEBUG and -O options. Run the program to compute fib(x) for various values of x, and make sure it writes the same output to stdout as the program built from C code does. Finally, run the program to compute fib(500000). In your readme file note the amount of CPU time consumed.
The givensimple.cfile defines a client of theBigIntmodule that is much simpler than the client defined byfib.c. If yourbigintadd.simplementation is failing tests performed by thefib.cclient, then you might find it helpful to debug using thesimple.cclient.
BigInt Objects Using Optimized Assembly Language CodeSuppose, to your horror, you discover that you have taken a step backward: the CPU time consumed by your assembly language code is approximately the same as that of the non-optimized compiler-generated code! So you decide to optimize your assembly language code...
Manually optimize your assembly language code in bigintadd.s, thus creating the file bigintaddopt.s. Specifically, perform these optimizations:
Store all parameters defined in the BigInt_larger and BigInt_add functions in caller-saved registers (where they are originally) instead of in memory. That is, use caller-saved registers throughout the definitions of the functions.
Store all local variables defined in the BigInt_larger and BigInt_add functions in callee-saved registers instead of in memory.
Use .equ directives to give meaningful names to:
Enumerated constants, for example: .equ TRUE, 1.
Registers that store parameters, for example: .equ OADDEND1, %rdi.
Registers that store local variables, for example: .equ ULCARRY, %r15.
Structure field offsets, for example: .equ LLENGTH, 0.
Build a fib program consisting of the files fib.c, bigint.c, and bigintaddopt.s using the -D NDEBUG and -O options. Run the program to compute fib(x) for various values of x, and make sure it writes the same output to stdout as the program built from C code does. Finally, run the program to compute fib(500000). In your readme file note the amount of CPU time consumed.
If yourbigintaddopt.simplementation is failing tests performed by thefib.cclient, then you might find it helpful to debug using thesimple.cclient.
Can you write assembly language code that is approximately as fast as the optimized code that the compiler generates? That is, can you approximately tie the compiler?
BigInt Objects Using Highly Optimized Assembly Language CodeFinally, suppose you decide to optimize your assembly language code even further, moving away from a statement-by-statement translation of C code into assembly language...
Further optimize your assembly language code in bigintaddopt.s, thus creating the file bigintaddoptopt.s. Specifically, perform these optimizations:
Use the assembly language loop patterns described in Section 3.6.7 of the Bryant & O'Hallaron book instead of the simpler but less efficient patterns described in precepts.
"Inline" the call of the BigInt_larger function. That is, eliminate the BigInt_larger function, placing its code within the BigInt_add function.
Use the adcq ("add with carry quad") instruction effectively. The adcq instruction computes the sum of its source operand, its destination operand, and the "carry" flag from the EFLAGS register, places the sum in the destination operand, and assigns 1 (or 0) to the "carry" flag if a carry occurred (or did not occur) during the addition. Effective use of the adcq instruction will use the "carry" flag in the EFLAGS register instead of a uiCarry variable to keep track of carries during addition.
Feel free to implement any additional optimizations you want. However, your BigInt_add function must be a general-purpose function for adding two given BigInt objects; the function cannot be specific to the task of adding two Fibonacci numbers to generate a third Fibonacci number. In other words, your function must work with the given fib.c client.
This part is difficult; we will not think unkindly of you if you decide not to do it. To do it properly you will need to learn about the adcq instruction, and about which instructions affect and do not affect the "carry" flag in the EFLAGS register.
Hint: When writing bigintaddoptopt.s, the problem is this: How can you preserve the value of the "carry" flag between executions of the adcq instruction? One solution is to save and then restore the value of the EFLAGS register. Another solution is to express the logic such that only instructions that do not affect the "carry" flag are executed between each execution of the adcq instruction.
Build a fib program consisting of the files fib.c, bigint.c, and bigintaddoptopt.s using the -D NDEBUG and -O options. Run the program to compute fib(x) for various values of x, and make sure it writes the same output to stdout as the program built from C code does. Finally, run the program to compute fib(500000). In your readme file note the amount of CPU time consumed.
If yourbigintaddoptopt.simplementation is failing tests performed by thefib.cclient, then you might find it helpful to debug using thesimple.cclient.
Can you beat the compiler?
Edit your copy of the given readme file by answering each question that is expressed therein.
One of the sections of the readme file requires you to list the authorized sources of information that you used to complete the assignment. Another section requires you to list the unauthorized sources of information that you used to complete the assignment. Your grader will not grade your submission unless you have completed those sections. To complete the "authorized sources" section of your readme file, copy the list of authorized sources given in the "Policies" web page to that section, and edit it as appropriate.
Provide the instructors with your feedback on the assignment. To do that, issue this command:
FeedbackCOS217.py 4
and answer the questions that it asks. That command stores its questions and your answers in a file named feedback in your working directory.
Submit your work electronically on CourseLab using these commands:
submit 4 mywc.s submit 4 mywc*.txt submit 4 performance submit 4 bigintadd.s submit 4 bigintaddopt.s submit 4 bigintaddoptopt.s submit 4 readme feedback
Comments in your assembly language code are especially important. Each assembly language function — especially the main function — must have a comment that describes what the function does. Local comments within your assembly language functions are equally important. Comments copied from corresponding flattened C code are particularly helpful.
Minimal requirement to receive credit for the "Translate to Assembly Language" (Part 1a) implementation:
The mywc.s implementation must build.
Minimal requirement to receive credit for the "Add BigInt Objects Using Assembly Language Code" (Part 2d) implementation:
The bigintadd.s implementation must build with fib.c and bigint.c using the -D NDEBUG and -O options.
Minimal requirement to receive credit for the "Add BigInt Objects Using Optimized Assembly Language Code" (Part 2e) implementation:
The bigintaddopt.s implementation must build with fib.c and bigint.c using the -D NDEBUG and -O options.
Minimal requirement to receive credit for the "Add BigInt Objects Using Highly Optimized Assembly Language Code" (Part 2f) implementation:
The bigintaddoptopt.s implementation must build with fib.c and bigint.c using the -D NDEBUG and -O options.
We will grade your work on two kinds of quality:
Quality from the user's point of view. From the user's point of view, your code has quality if it behaves as it must. The correct behavior of your code is defined by the previous sections of this assignment specification.
Quality from the programmer's point of view. From the programmer's point of view, your code has quality if it is well styled and thereby easy to maintain. Good program style is defined by the previous section of this assignment specification.
To encourage good coding practices, we will deduct points if gcc217 generates warning messages.
Testing is a substantial aspect of the assignment. Approximately 10 percent of the grade will be based upon your mywc test plan as described in your readme file and as implemented by your data files.
Your grade for Part 2f will be based upon:
Raw performance (5 percent). That is, how quickly does your code compute fib(500000)? We can't award any raw performance points unless your code passes all tests in the fib.c client.
Style (6 percent). That is, does your code contain optimizations that logically should improve performance?
This assignment was written by Robert M. Dondero, Jr.,
based in part upon suggestions from Andrew Appel.