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Data hazard detection in assembly code

Open Ram-Aditya opened this issue 6 years ago • 0 comments

Description

  • Write a program to analyze an assembly program and detect RAW( read after write ), WAR( write after read ) and WAW( write after write ) data hazards in a simple assembly code for a pipelined instruction execution.
  • The sample assembly code that is to be used as input is present in the testing_prog.txt file in the /systems/assembly/data_hazard_detection directory.
  • Assume that the assembly language consists of only the following instructions: add, mul, mov, load.
  • The syntax of the assembly language is: instruction destination, source/operands
  • The expected output is list of pairs of instructions with the type of data hazard that is present between them.
  • Consider the given assembly code as it is and do not be concerned about what the assembly code as a whole is actually trying to solve/calculate.

Details

  • Technical Specifications:
    • A total of 4 implementations will be accepted.
  • Type of issue: No more than one implementation will be accepted for each language. Once the implementation for a language has been taken up you must choose a different language.
  • Time Limit: The claim for the issues will be given on a first-come, first-serve basis. Once you take this issue up in a particular language, you must complete it within 3 days, failing which the issue will be allocated to the next person who requested for this issue.

Issue Progress - Languages that have been claimed

Will be updated as and when the issue is claimed.

Resources

http://web.cs.iastate.edu/~prabhu/Tutorial/PIPELINE/dataHazClass.html

Directory Structure

For this issue, use the following directory of the Hacktoberfest-2k18 repository: /systems/assembly/data_hazard_detection/language_name (where language_name is the language that your program has been written in.)

Note

Please claim the issue first by commenting here before starting to work on it. Please mention in which language you would like to implement the program in.

Ram-Aditya avatar Oct 18 '18 09:10 Ram-Aditya