1. TORNADO OPERATING SYSTEM
Karan Sharma

2. Tornado - Overview Object–Oriented Approach Clustered Objects
Semi-automatic Garbage Collection
Protected Procedure Call

3. The Problem
Locality and Concurrency based approaches that are successful for Uniprocessors do not necessarily scale to Multiprocessors
Efficient management of locality and concurrency is necessary in multiprocessors

4. The Problem Problems with modern multiprocessors
Higher memory latencies
Large write sharing costs,
Large secondary caches,
Large cache lines
NUMA effects, and
Larger system sizes

5. The Problem (The Counter Experiment)
Counter Implementations
Shared, Array, Padded Array, Clustered Object
How the Number of Processors effect the Cycles per update of a Counter, for each type of Counter?
- Can give insight into locality issues in
multiprocessors

6. The Problem (The Counter Experiment)

7. The Problem (The Counter Experiment)
Take Home Message:
Avoid Sharing!
There is a significant and substantial connection between ”how you tackle locality” and ”performance of the system” (in a multiprocessor system)

8. Object Oriented Approach
“To achieve good performance on a multiprocessor, requests to different virtual resources should be handled independently; that is, without accessing any shared data structures and without acquiring any shared locks. One natural way to accomplish this is to use an object-oriented strategy, where each resource is represented by a different object in the operating system.”

9. Object Oriented Approach
User Application
OS Implementation
Locality
Locality
Independence
Independence
Philip Howard’s Illustration

10. Object Oriented Approach (Memory Management Example)

11. Clustered Objects What do they look like? Outside View
Just like your normal Java/C++ - style objects
Inside View
Consists of many Representative Objects (rep) where each rep may belong to several processors

12. Clustered Objects

13. Clustered Objects Advantages
Optimizations such as Replication or partitioning
Clean Interface
Incremental Optimization
Several Different implementations may exist

14. Degree of Clustering
(Appavoo 1998)

15. Clustered Objects
Appavoo 1998

16. Clustered Objects
(Gamsa 1999)

17. Clustered Object Implementation
Reps are created on demand because it is not known what reps will be invoked
On first invocation, this is accomplished by:
Global Miss Handling Object ->
Clustered Object’s Miss Handler ->
Create a rep Or
Locate a rep (if it’s already there)
Install a pointer to this rep in the translation table
On subsequent invocations, the rep will be called directly

18. Clustered Objects

19. Synchronization Spin-then-block locks
Semi-automatic Garbage Collection
Temporary References
Persistent References

20. Protected Procedure Call
(Gamsa 1999)
Recall LRPC

21. Protected Procedure Call (Advantages)
client requests are always serviced on their local processor
clients and servers share the processor in a manner similar to handoff scheduling
there are as many threads of control in the server as client requests.

22. Results

23. Tornado - Impact
Does not seem to have explicitly impacted many of the popular operating systems
However, many of the ideas have gone into IBM’s K42 - The next generation of Tornado

24. ANY QUESTIONS?