# CS 4290 / CS 6290 / ECE 4100 / ECE 6100 Lab 1: Analyzing Benchmark Traces and Computing CPI solution

\$30.00

Original Work ?

5/5 - (1 vote)

## OBJECTIVE:

The objective of the first lab assignment is to test the proficiency of students in
doing programming-based assignments and to ensure that the students have the basic
background in computer architecture to take this graduate-level course.

The assignment is
due before the Phase II registration deadline (Friday), so that the students can make wellinformed decisions whether they should continue with the course or should consider taking it
after getting the required prerequisites.

Given the lab’s purpose, students are expected to be
able to confidently complete it without any help from TAs. We will provide an autograder for this
assignment, so that you can estimate the score your submission is likely to receive at the time
of submission.

## PROBLEM DESCRIPTION:

The first lab assignment’s goal is the analysis of the static and
dynamic instruction occurrences in a given benchmark trace. We will provide a code template
and traces from four benchmarks (gcc, mcf, libquantum, and bzip2) selected from the SPEC
CPU2006 suite. We will also provide a trace reader for these traces.

following:
Task 1: Quantify the mix of the dynamic instruction stream. The instructions in the trace are
classified as five types: ALU, LOAD, STORE, CBR (Conditional Branch), and OTHER. You will
modify the provided code to count the number of dynamic instructions for each category and the
percentage of these instruction types in the instruction mix.

Task 2: Estimate the overall CPI (Cycles Per Instruction) using a simple CPI model in which the
CPI for each category of instructions is provided. We will use the following CPI for each
category:
1) ALU: 1
3) Store: 2
4) CBR: 3
5) Other: 1

Note: As the instruction mix for each trace is likely to be different, the CPI for each trace is likely
to be also different.

Task 3: Estimate the instruction footprint by counting the number of unique PCs in the
benchmark trace. Normally, this information should be multiplied by the average bytes per
instruction to get the total footprint, however for this lab we will forego this multiplication.

HOW TO GET STARTED:
2. “tar -xvzf Lab1.tar.gz”
3. “cd Lab1”
4. “ls” — Lab1 contains four subdirectories: src, scripts, traces, and results.
5. “cd src”
6. “ls” (there are three files: makefile, trace.h, sim.cpp)

print functions. Your objective is to simply write the function analyze_trace_record() and
update the stats variable (stat_*).

8. Once you write the function, type “make” … this should create an executable “sim”.
9. “./sim ../traces/bzip2.otr.gz” (to run one trace and see the output).
10. Perform a sanity check on the output to verify whether it makes sense or you need to

11. Once your code is ready, go to the scripts directory “cd ../scripts”.
12. “./runall.sh” — this runs your code for all four traces, stores the result files in the results
directory and also generates the “Report.txt” file.

13. The last line of the report file is your approximate score out of 5 points. Note that we will
run your source code on a separate set of “hidden” traces, so your graded score may be
different if your implementation is incorrect.

REFERENCE MACHINE:
We will use the virtual machine oortcloud.cc.gatech.edu as a test machine for this course.
You should be able to connect to it using ssh and transfer files between oortcloud and your local
machine using scp. If you are not officially enrolled in the course yet, you may not be able to
access the machine. In that case, make sure that your code works on a standard Linux
machine. We will be compiling and running your lab submissions using an autograder on
Gradescope (based on this docker image). We recommend using oortcloud for
testing/debugging and submitting to gradescope for checking the points.

machine and generates the desired output (without any extra printf statements). Please follow
the submission instructions. If you do not follow the submission file names, you will not receive
full credit.

NOTE 1: It is impractical for us to support other platforms such as Mac, Windows, Ubuntu etc.
Due: Friday, August 25, 11:55pm

HOW WELL DID YOU DO? If you have the right background, this lab should take about 1-2
hours to complete. If this lab assignment takes you 5-10 hours or more, you may not have the
right background for this course. Labs 2, 3 and 4 will each likely take about 10x more time and
are about 10x harder. So, if you do not have the right background, you may find the
assignments for this course to be extraordinarily difficult.

We strongly recommend that you use a private git repository to version-control your code and
prevent any loss. You should never assume that any code/data stored on a local machine (your
laptop, desktop, or even the oortcloud machine) are safe. Although data loss is very rare, you
should always follow best practices to completely eliminate that chance. We will not accept
incidents like “my laptop broke down/oortcloud was wiped and I lost all my progress” as a valid
excuse for late homework submission.

FAQ:
1. /usr/bin/ld: cannot find -lz collect2: error: ld returned 1 exit status
Please remove the ‘-lz’ flag from the Makefile or install zlibc on your system.
2. How do I connect to the reference machine?
a. You will need to connect to VPN using a VPN client to access most machines at
GT: https://faq.oit.gatech.edu/content/how-do-i-get-started-campus-vpn
b. An ssh client (e.g., Putty SSH) to connect from your machine to the reference
machine.
c. SCP for file transfers to/from the server. There are several scp GUI tools
available or you can directly execute the command from the terminal
(https://linux.die.net/man/1/scp).
3. Why can’t I execute the runall.sh script?
Check that you have execute permissions on the file. Add execute permissions to
runall.sh and genreport.oortcloud using chmod +x.