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Computer Hardware Optimization

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Presentation on theme: "Computer Hardware Optimization"— Presentation transcript:

1 Computer Hardware Optimization
By Seth Register and Ethan Ingalls Computer Hardware Optimization S

2 Introduction Deciding the best possible hardware for one’s money is often tedious. Combined original idea of video card optimization and TSP. More resources for TSP!! S

3 What does our program do?
Takes a set of inputs: GPU: RAM: CPU: HDD: GPU#1 RAM#1 CPU#1 HDD#1 GPU#2 RAM#2 CPU#2 HDD#2 GPU#3 RAM#3 CPU#3 HDD#3 With a cost constraint Finds the ideal single combination Can choose which algorithm to run E

4 Formal Statement: Given a set of finite computer hardware(inputs) and a cost constraint, find the combination of CPU, GPU, RAM, and HDD with the highest score in the lowest amount of time. S

5 Benchmarks Scores from FutureMark They use 3DMark software
Set creation from a known set S & E

6 Brute Force: Try EVERYTHING!!! Very accurate Takes a long time O(n4) E

7 Results: Score vs number of inputs: Time vs number of inputs:
(Yaxis = Score, Xaxis = inputs) (Yaxis = Time, Xaxis = inputs) At 100 inputs score was: At 100 inputs time was: 0.3 seconds At 500 inputs score was: At 500 inputs time was: seconds E

8 Greedy As lazy as possible If there is enough money, adds the cheapest
GPU, CPU, RAM, and HDD. Keeps adding one until the money runs out. S

9 Results Score vs number of inputs: Time vs number of inputs:
At 100 inputs score was: At 100 inputs time was: 1 (ms) At 500 inputs score was: At 500,000 inputs time was: 57ms seconds (Yaxis = Score, Xaxis = inputs) (Yaxis = Time, Xaxis = inputs) S

10 Modified Brute Force Accuracy is the same as Brute Force
Time is reduced on tight constraints Has two checks to avoid unnecessary iterations E

11 Results: Score vs number of inputs: Time vs number of inputs:
(Yaxis = Score, Xaxis = inputs) (Yaxis = Time, Xaxis = inputs) At 100 inputs score was: At 100 inputs time was: 0.15 seconds At 500 inputs score was: At 500 inputs time was: 88.6 seconds E

12 Conclusion Time: Brute Force vs Greedy vs MBF Score: 100 0.3 seconds
1 ms 0.15 seconds 500 168 seconds 88.6 seconds 500,000 Null 57 ms ~Null/2 100 86923 41801 500 437240 166100 S & E

13 Future Work Add more inputs
Allow for some inputs to be omitted during the search Print an image of the resulting hardware with buy links S

14 Why 380? Learned, designed, and implemented three algorithms
Accuracy vs Practicality Created an awesome program! E & S

15 Questions: 1. What is the difference between the Brute Force and Modified Brute Force, and how does it affect their time complexities? 2. What are two problems when using Greedy algorithm? 3. Why would a Greedy algorithm ever be used? 1)MBF has checks to eliminate unnecessary iterations Creates an average case about half of BF 2) Least accurate Depends on which input is first in the code 3)With high amount of inputs


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