Upcoming SlideShare
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Standard text messaging rates apply

# parallel computing

331

Published on

Published in: Technology
0 Likes
Statistics
Notes
• Full Name
Comment goes here.

Are you sure you want to Yes No
• Be the first to comment

• Be the first to like this

Views
Total Views
331
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
20
0
Likes
0
Embeds 0
No embeds

No notes for slide

### Transcript

• 1. 1
• 2. K.NARAYANA08Q61A0575 2
• 3. ExecutionEXAMPLE :-• main(){• for (int i = 0; d.get_meaning(i,s) != 0; ++i)• cout << (i+1) << ": " << s << "n";• return 0;}
• 4. 4
• 5. 5
• 6. For example:
• 7. Traditionally software has been written for serial computation. 7
• 8. 8
• 10. 11
• 11. Parallel Computer Memory Architectures:
• 12. Parallel Computer Memory Architectures: Distributed Memory
• 13. There are different ways to classify parallel computers• classified along the two independent dimensions of Instruction and Data• SISD – Single Instruction, Single Data• SIMD – Single Instruction, Multiple Data• MISD – Multiple Instruction, Single Data• MIMD – Multiple Instruction, Multiple Data
• 14. SISD 15
• 15. SIMD 16
• 16. MISD 17
• 17. MIMD 18
• 18. ADVANTAGES•In the simplest sense, parallel computing is To be run using multiple CPUs A problem is broken into discrete parts that can be solved concurrently Each part is further broken down to a series of instructions Instructions from each part execute simultaneously on different CPUs
• 19. Parallel computingOverheads  Synchronization  Problem decomposition  Data Dependencies 20
• 20. 21
• 21. Problem decomposition
• 22. Data Dependencies• 1: function Dep(a, b) • 1: function NoDep(a, b)• 2: c := a·b • 2: c := a·b• 3: d := 3·c • 3: d := 3·b• 4: end function • 4: e := a+b • 5: end function
• 23. Conclusion• Parallel computing is fast.• There are many different approaches and models of parallel computing.• Parallel computing is the future of computing.• Solve larger problems
• 24. 25