Software solutions for challenges in embedded systems Sri Hari Krishna Narayanan, The Pennsylvania State University, USA, [e-mail]

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Software solutions for challenges in embedded
systemsSri Hari Krishna Narayanan, The
Pennsylvania State University, USA,
snarayan_at_cse.psu.edu
Temperature crisis alleviation in CMPs and NoCs
Cycle Times
Temperature Sensitive Schedule
Scheduler
HotSpot
Chunk Sizes
Phase 3 Locality Based Scheduling
Scheduler
Energy Consumption
Phase 2 -Temperature Sensitive Scheduling
Architecture Details
Temperature Locality Sensitive Schedule
Code Generator
Omega Library
Phase 4 - Code Generation

• Challenge To prevent chips from overheating
• Solution
• On chip temperature rises when the chip is run
  continuously at high power density.
• Develop a schedule that allows processors to
  cool down in between executing portions of the
  task.
• Such a schedule is possible because applications
  do
• not make use of all the processor cores
  available.

• Challenge To prevent NoC based chips from
  overheating
• Solution
• On chip temperature rises through high power
  density.
• Applications typically do not use all the
  available processor cores
• Design a task to processor mapping that reduces
  the power density.

Theme While hardware solutions to challenges in
embedded systems are very important, software
can also play an important role. Software
techniques to solve three important problems are
presented here.
Percentage of Execution during which a thermal
emergency is experienced.
Normalized execution time.
The graphs show how the peak on chip
temperature is always maintained below a preset
threshold that is indicated by the solid line.
Securing code semantics
Soft Error Detection
Traditional computing
Mobile computing
Original Code
Original Code
Original Results
Original Results
Original Results
Challenge To prevent an untrusted host from
gleaning the semantics of the clients code.
i.e. to prevent reverse
engineering. Solution Translation of the
original code produces a new code that
a) is semantically different,
b) accesses data in a different
pattern, and c) whose stores
take place to different locations.

• Challenge To detect single event upsets in the
  data caches.
• Solution
• Invariants are data properties that must hold
  throughout the execution.
• Checking to see if they hold true during
  execution, gives and indication of whether the
  execution was successful of if a soft
• error occurred.

Mobile computing with code level transformations
Data
Original Code
Transformed Code
The increase in code size due to checker code
The soft error detection rate

• References
• Sri Hari Krishna N., M. Kandemir, R. R. Brooks,
  I. Kolcu. Secure Execution of Computations in
  Untrusted Hosts, in the proceedings of ADA-EUROPE
  2006.
• Sri Hari Krishna Narayanan, Mahmut Kandemir.
  Compiler-Directed Power Density Reduction in
  NoC-Based Multi-Core Designs, in the proceedings
  of ISQED 2006.
• Sri Hari Krishna Narayanan, Guilin Chen, Mahmut
  Kandemir, Yuan Xie. Temperature-Sensitive Loop
  Parallelization for Chip Multiprocessors, in the
  proceedings of ICCD 2005.
• Sri Hari Krishna N., Seung Woo Son, M. Kandemir,
  Feihui Li. Using Loop Invariants to Fight Soft
  Errors in Data Caches, in the proceedings of
  ASP-DAC 2005.

Original Results