Difference between revisions of "Fibonacci"
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=Motivation= | =Motivation= | ||
− | It is important to always reduce the work, then parallelize if possible. In this studio you will build a beautiful, elegant solution to Fibonacci which can be easily parallelized yielding off-the-charts ideal parallelism. Sadly, it performs terribly since the work is exponential <math>\Phi^N</math>. It is far better to build a linear time or log time algorithm | + | It is important to always reduce the work, then parallelize if possible. In this studio you will build a beautiful, elegant solution to Fibonacci which can be easily parallelized yielding off-the-charts ideal parallelism. Sadly, it performs terribly since the work is exponential <math>\Phi^N</math>. It is far better to build a linear time or log time algorithm independent of if can or cannot be parallelized. |
We will convert recurrence relations into code. | We will convert recurrence relations into code. |
Revision as of 19:51, 5 February 2018
Contents
Motivation
It is important to always reduce the work, then parallelize if possible. In this studio you will build a beautiful, elegant solution to Fibonacci which can be easily parallelized yielding off-the-charts ideal parallelism. Sadly, it performs terribly since the work is exponential . It is far better to build a linear time or log time algorithm independent of if can or cannot be parallelized.
We will convert recurrence relations into code.
Additionally, (and of minor importance) We gain experience with the BigInteger class.
Background
The fibonacci sequence is a mathematical concept often used in computer science as a means to demonstrate iteration and recursion. Although you should be familiar with it from CSE 131, we will use the fibonacci sequence to demonstrate memoization and dynamic programming. Follow these links for a quick recap on memoization, dynamic programming, and the fibonacci sequence.
Where to Start
You will need to return the number associated with a given position in the fibonacci sequence. For example, if 0 was fed in, the method should return 0. 1 should return 1, 2 should return 1, 3 should return 2, and so on.
JUnit Test Suite
FibonacciTestSuite
Javadocs
Common Mistakes To Avoid
use Habanero's HjFuture<V>, NOT java.util.concurrent's Future<V>
Check out Habanero#Future for pointers on using Habanero's futures.
use long, NOT int
lambdas will get cranky if you try to return an int instead of a long.
also, if you use ints in your calculation you will fail the tests when the result goes over Integer.MAX_VALUE.
Studio (Required)
RecurrenceRelationSequentialFibonacciCalculator
class: | RecurrenceRelationSequentialFibonacciCalculator.java | |
methods: | fibonacci | |
package: | fibonacci.studio | |
source folder: | student/src/main/java |
implement a recursive method for:
recurrence relation
seed values
RecurrenceRelationParallelFibonacciCalculator
class: | RecurrenceRelationParallelFibonacciCalculator.java | |
methods: | fibonacci | |
package: | fibonacci.studio | |
source folder: | student/src/main/java |
Use futures to add parallelism to the recurrence relation solution.
MemoizationSequentialFibonacciCalculator
class: | MemoizationSequentialFibonacciCalculator.java | |
methods: | fibonacciMemo | |
package: | fibonacci.studio | |
source folder: | student/src/main/java |
Implement the recurrence relation algorithm but employ memoization for the win.
DynamicIterativeSequentialFibonacciCalculator
recurrence relation
- if n is odd
- else
seed values
Fun (Optional)
DynamicRecursiveSequentialFibonacciCalculator
LinearRecurrenceSequentialFibonacciCalculator
MemoizationParallelFibonacciCalculator
Create all of your futures [0..N] up front and then call get on memo[n].
RoundPhiToTheNOverSqrt5SequentialFibonacciCalculator
Testing Your Solution
Correctness
class: | FibonacciTestSuite.java | |
package: | fibonacci.studio | |
source folder: | testing/src/test/java |
Performance
class: | FibonacciIterations.java | |
package: | fibonacci.studio | |
source folder: | src/main/java |