~sumner/aca-project3

CSCI 564 Advanced Computer Architecture Project 3 Description and Starter Code
branch_predictors.h: fix docs on handle_result
tests: add trace4 and associated expected
grader script: updated weights to reflect Gradescope grader script

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#Project 3 -- Branch Prediction Simulator

This is an individual project. You may only collaborate with your classmates according to the CS Collaboration Policy. Plagiarism will be punished severely.

#Learning Objectives

  • Create a branch prediction simulator.
  • Become familiar with static branch predictors.
  • Become familiar with last-time and two-bit branch predictors.
  • Become familiar with the difference between global and local branch prediction.

#Overview

In this project, you will create a branch prediction simulator which can be used to observe (a) how different branch prediction policies affect branch prediction accuracy, and (b) how global/local branch prediction affects branch prediction accuracy.

It is highly recommended that you develop this project on a Linux system. If you choose to use a different type of system (such as macOS or Windows), the instructors and TAs will not be able to assist you with any platform-specific issues.

#Rubric

This project is worth 150 points, distributed as follows:

# Item Points
1.1 Always not-taken (ANT) branch predictor* 5
1.2 Always taken (AT) branch predictor* 5
1.3 Backwards taken, forwards not-taken (BTFNT) branch predictor* 20
2.1 Last-time global (LTG) branch predictor* 25
2.2 Last-time local (LTL) branch predictor* 35
3.1 Two-bit global (2BG) branch predictor* 25
3.2 Two-bit local (2BL) branch predictor* 35
TOTAL 150

* indicates that the rubric item is auto-graded

NOTE: Since your submission will be partially auto-graded on Gradescope, you will be only be allowed a total of three submissions. Be sure to test your code before submitting!

#Branch Predictor Simulation

Your simulator must simulate a branch prediction system with a variety of branch prediction strategies.

#Branch Predictor Behavior

The following describes how the simulation must behave. Note that some of this functionality is already implemented by the starer code.

Assumptions:

  • At the start of the simulation, all prediction counters are initialized to NOT_TAKEN
  • At the start of the simulation, all global and local history registers are initialized to all zeros.
  • The branch target buffer (BTB) is infinite. In other words, the branch predictor always knows the branch target.
  • For global branch predictors:
    • The global history register (GHR) holds 5 bits of history. Thus the PHT holds 32 entries.
  • For local branch predictors:
    • There are 16 local history registers (LHRs), indexed by the 4 least-significant bits of the program counter (instruction address).
    • Each local history register (LHR) holds 4 bits of history.
    • Each LHR has its own pattern history table (PHT).

For each branch:

  1. The branch predictor is called and provides a prediction as to whether the branch is taken or not taken.

  2. If the branch prediction was correct, then the correct prediction count is incremented.

  3. The branch predictor gets updated with the actual result of the branch.

#Branch Predictors

You must implement the following branch predictors.

  • ANT (Always Not Taken, item 1.1 in the rubric) --- always predict the branch will not be taken.
  • AT (Always Taken, item 1.2 in the rubric) --- always predict the branch will be taken.
  • BTFNT (Backwards Taken, Forwards No-Taken, item 1.3 in the rubric) --- predict that backwards branches (where the target PC < instruction PC) are taken and forwards branches are not taken.
  • LTG (Last-Time Global, item 2.1 in the rubric) --- a two-level global branch predictor with a pattern history table consisting of 1-bit counters.
  • LTL (Last-Time Local, item 2.2 in the rubric) --- a two-level local branch predictor with a pattern history table consisting of 1-bit counters.
  • 2BG (2-Bit Global, item 3.1 in the rubric) --- a two-level global branch predictor with a pattern history table consisting of 2-bit counters.
  • 2BL (2-Bit Local, item 3.2 in the rubric) --- a two-level local branch predictor with a pattern history table consisting of 2-bit counters.

#Input Format

The branch trace input will be passed via stdin. It has two sections: the branch target metadata and the branch trace.

Branch Target Metadata:

The first line of the file contains N, the number of unique branch instructions there are in the trace. The next N lines contain metadata about those unique branch instructions. Each of those lines are formatted as two space-separated values that indicate the instruction address and the branch target address, respectively.

Branch Trace:

The rest of the file consists of branch traces formatted as two space-separated values that indicate the instruction address and whether the branch was taken or not taken, respectively.

You are guaranteed that the instruction addresses in this part of the file have corresponding entries in the branch target metadata part of the file.

Example:

(Note, the text after the #s are just for explanation purposes, and are not actually part of the input.)

4               # number of branches
0x004 0x000     # (instruction address) (branch target)
0x040 0x044
0x04c 0x044
0x080 0x044
0x004 TAKEN     # (instruction address) (taken/not-taken)
0x004 TAKEN
0x004 TAKEN
0x004 NOT_TAKEN

#Starter Code Overview

The starter code provides a C project that can be compiled using make. The only dependency for compiling the code is GCC.

The starter code should compile as-is, however it will not behave correctly. I recommend that you attempt to build the starter code before starting to make your own modifications so that you know that you have something that is working.

The starter code provides an easy way to create a properly formatted submission TAR.GZ file using make submission. This calls the bin/makesubmission.sh script. This script requires sh and tar.

Note for Nix package manager users: a shell.nix file is provided with the starter code. Running nix-shell will start a shell with the necessary dependencies installed. If you also use direnv, running direnv allow will add of the environment variables from the Nix shell to your current environment when you cd to this directory.

#Downloading the Source

If you want to use git on this project, please use a private repo. Then, run the following commands to clone the starter code and set the origin to your repo:

git clone https://git.sr.ht/~sumner/aca-project3
git remote set-url origin <your-private-repo-url>

Alternatively, if you don't want to use Git, you can download a TAR.GZ of the source from the following URL: http://git.sr.ht/~sumner/aca-project3/archive/master.tar.gz

#Building and Running

You can build the starter code by running make from this directory. This will create a branchsim executable that you can run. See the Inputs section for details on what inputs need to be passed in and what the parameters are.

You can also run the automated test script which includes some of the inputs that will be run by the grader script by running the following command:

$ make grade

This will compile your program and then run the grader script. The grader script requires Python 3 and scipy.

#Top-Level Organization

The following tree shows an overview of the important files and directories in the starter code repository.

/aca-project3                   project root
|-> bin/                        contains some utility shell scripts
|-> expected/                   contains expected outputs
|-> inputs/                     contains a set of sample input trace files
|-> Makefile                    a Makefile for compiling the project
|-> README.md                   this README file
'-> src/                        all of the source code for the project

#Source Organization

All of the places where you potentially need to add code are marked with a TODO. All of the TODOs are in src/branch_predictors.c.

There are extensive comments at the top of each file explaining what each one does. There are also comments throughout the code explaining in detail the most important parts of the codebase.

The src/util.h and corresponding src/util.c provide a nice binary print function that prints the N least-significant bits of a given integer. This function will likely be helpful for debugging.

#Full Requirements

The following requirements are automatically fulfilled by the starter code (assuming correct usage). They are included so that if you choose to write your simulator without using the starter code, your submission will be able to be graded.

#Compilation and Runtime Environment

Your submission must compile and run on Ubuntu 18.04 and the execution of the simulator must not utilize any network resources. The compilation process may utilize network resources only for downloading any compilers required to compile your program. Your program must not error on any well-formed inputs, and must exit with 0 as the exit code. If the input is malformed, the behavior of the program is undefined.

If your submission fails to compile or run on Ubuntu 18.04 without using network resources during execution, you will receive a score of 0 for this project.

#Submission Format

Failure to follow the submission format described in this section will result in a score of 0 for this project.

You must submit a TAR file with all of your source code. The TAR file can optionally be XZ or GZ compressed. The filename of your submission must match the following regular expression (case is ignored):

(\w+)-project3.(tar(.gz|.xz)?)
-----              ---------
  ▲                      ▲
your MultiPass username  |
                         |
                     optional compression of TAR file

Your TAR file must contain a Makefile in the root of the archive. Running make should compile your code and create an executable file called branchsim in the same directory as the Makefile. This executable must be your branch prediction simulator implementation.

#Inputs

Your program must accept four positional command line arguments:

  • Branch Predictor Type: this will be one of the following: ANT, AT, BTFNT, LTG, 2BG, LTL, or 2BL, representing the branch predictor to use in the simulation.

Your program must accept a trace of branches via stdin as described in Input Format.

Example execution with the LTG branch predictor and passing the contents of the ./inputs/trace1 file via stdin.

$ ./branchsim LTG < ./inputs/trace1

#Output

Your program must provide output on stdout. Output to stderr or to a file will not be graded.

Additionally, only lines that start with OUTPUT will be graded. This means that you can output as much as you want to stdout for debugging purposes as long as those lines don't begin with OUTPUT.

#Statistics Output

The OUTPUT lines that are required are the statistics output which should be printed after the simulation is complete. Specifically, the following statistics must be output in order:

  • Predictions (int): the total number of branch predictions made
  • Correct (int): the total number of correct branch predictions
  • Incorrect (int): the total number of incorrect branch predictions
  • Branch Prediction Rate (float): the ratio of correct predictions to total predictions (formatted with 8 decimal places and a leading zero).

Each of the statistics should be its own line, and should be written in all caps. For example:

OUTPUT PREDICTIONS 150
OUTPUT CORRECT 138
OUTPUT INCORRECT 12
OUTPUT BRANCH PREDICTION RATE 0.92000000

#Other Instructors

You are free to use or adapt this project for your course. If you are interested in my solution or autograder code, please email me at me [at] sumnerevans [dot] com.

#Contributing

Contributions to this project description or to the starter code are welcome!

If you find an issue with the project description or to the starter code or want to suggest an improvement to it, please submit a patch via git-send-email to the ~sumner/public-inbox mailing list or send the patch directly to me. You can also send an email to the mailing list to discuss potential changes.

#Credits

  • README and starter code developed by Sumner Evans.
  • Thanks to Adam Sandstedt for testing the assignment and creating most of the input-output pairs.