CONTACT:RABI@CSE.TAMU.EDU
 

Assignments

The assignments will be posted here with details on their due dates. ALL assignments are to be turned in by e-mail. No hardcopy please.

For some reasons if you are unable to submit any assignment by the deadline, you need to inform your instructor a priori. All the assignments will be graded. At the end, one of the lowest scored assignment may be excused from grading if you have turned in all the assignments. Late assignments without permission will have penalty @25% per each late day.

 

 Assignments Due Date 
 Assignment 0Basics on Interrupt HandlerTutorial on Three Cycle High  20-SEP-2016
 Virtual Prototype Assignment 1  Optional
 Reading Assignment:Read the paper on Power-Aware Multicore Simulation on the Schedule below and give 1-2 page review that includes. Simulator capabilities,  accuracy vs run time, scalability issues of SoC, benchmarks, potential challenges using it and setup details.Also Refer:  http://snipersim.org/w/The_Sniper_Multi-Core_Simulator for more details.Deadline:This is an individual assignment. You can always collaborate in discussion with others.
 Virtual Prototype Assignment 2    Due: TBA  Optional
 Virtual Prototype Assignment 3    Due: TBA  Optional
 Virtual Prototype Assignment 4   Due: TBAMxScript Tutorial (Assignment5) Due: TBA (ignore two week mark on the assignment)  Optional

Alternate Assignment 2: Read the following paper. Prepare 1-2 page summary and about 20 slides (max) pptx version. Check additional recent references on Co-synthesis and include them as references. Deadline Optional.

http://ecee.colorado.edu/~shangl/papers/shang07mar.pdf

 

Assignment 5: Explore a Data Analytic Case Study from literatures of your own. Prepare a technical report with following details (no slides). DL: TBA

1. Domain specification and objectives of the case study,(i.e. data types: streaming/static, simple or predictive, etc..)

2. Basic steps involved in the study. (cleaning, pre-processing, optimization, visualization etc; kind of classifications, algorithms, techniques used with details)

3. Identify data sources (synthetic, real, website, scale, etc including benchmarks). Give cross references if any. open or private data? If private, find similar data set from open sources,

4. Parameters that were analyzed: identify target specific goals. Then suggest what more analysis can be feasible and how based on what you see the literature.

5. Identify the challenges the existing system or the work has faced or the limitations there in. Suggest how to improve them.

Reading Reference on Data Analytic Benchmark: This is an example research. You will be using different example/domain/case studies though.

http://www.hpl.hp.com/techreports/2014/HPL-2014-75.pdf

If you can’t open it let me know.