Solve task on 7th Parallel Marathon Competition

1. Lab: FCDS - midterm presentation
Ruochun Tzeng

2. OpenMP
● Memory Model: Shared-Memory
● Execution Model: Fork-Join
#pragma omp parallel num_threads(4)
{
hello();
}
// logically equivalent code
void thunk() {
hello();
}
pthread_t tid[4];
for (int i=1; i<4; ++i)
pthread_create(&tid[i], 0, thunk, 0);
thunk();
for (int i=1; i<4; ++i) pthread_join(tid[i]);
compiler directives
compiler

3. OpenMP
● Memory Model: Shared-Memory
● Execution Model: Fork-Join
#pragma omp parallel num_threads(4)
{
hello();
}
// logically equivalent code
void thunk() {
hello();
}
pthread_t tid[4];
for (int i=1; i<4; ++i)
pthread_create(&tid[i], 0, thunk, 0);
thunk();
for (int i=1; i<4; ++i) pthread_join(tid[i]);
compiler directives
compiler

4. OpenMP
● Memory Model: Shared-Memory
● Execution Model: Fork-Join
#pragma omp parallel num_threads(4)
{
hello();
}
// logically equivalent code
void thunk() {
hello();
}
pthread_t tid[4];
for (int i=1; i<4; ++i)
pthread_create(&tid[i], 0, thunk, 0);
thunk();
for (int i=1; i<4; ++i) pthread_join(tid[i]);
compiler directives
compiler

5. OpenMP
● Memory Model: Shared-Memory
● Execution Model: Fork-Join
#pragma omp parallel num_threads(4)
{
hello();
}
// logically equivalent code
void thunk() {
hello();
}
pthread_t tid[4];
for (int i=1; i<4; ++i)
pthread_create(&tid[i], 0, thunk, 0);
thunk();
for (int i=1; i<4; ++i) pthread_join(tid[i]);
compiler directives
compiler

6. OpenMP
● Data Parallelism
– #pragma omp parallel for
for(i=0; i<MAX; i++)
...
● Task Parallelism
– #pragma omp section
thread1 thread2 thread3 thread4sequential

7. OpenMP
● Data Parallelism
– #pragma omp parallel for
for(i=0; i<MAX; i++)
...
● Task Parallelism
– #pragma omp section
thread1 thread2 thread3 thread4sequential
A
B
C
D
A B
C
D
#pragma omp sections
{
{ A(); }
#pragma omp section
{ B(); C();}
#pragma omp section
{ D(); }
}

8. OpenMP
● Others(recursive, irregular)
– Try #pragma omp task

9. Task Overview
● Tried 4 of 5
– Bucketsort
● Faster than seq and scaled to medium input
– Unbounded Knapsack Problem
● Faster than seq and scaled to largest input
– 3-SAT
● Better than seq, but not scaled
– Mutually Friendly Number
● Slower than seq, not scaled

10. Bucketsort
● N = 10^10, #Bucket = 94
1. Putting items to local buckets
2. Sort individually
3. Merge local buckets into shared bucket
– current: non-inplace merge
● Experiment
– Medium input (10^7) tested
– Large input(10^10) not complete the test

11. Bucketsort
#thread

12. ● N < 1024, M < 10^6
● Dynamic programming works
for (int i=0; i<n; ++i)
for (int j = weight[i]; j <= w; ++j)
c[j] = max(c[j], c[j - weight[i]] + cost[i]);
Unbounded Knapsack
c[j]: the max value I could have with capacity at most up to j
take item inot to take item i
// Update to c[j] is atomic
#pragma omp parallel for

13. Unbounded Knapsack
sequential: > 14 hours
#thread

14. ● V1: just parallel seq code → slower than seq
● V2: random assign variables
– #trial = 10^10, true negative = 50%
→ not acceptable at all
● V3: dfs (clause by clause) + little opt
– C = (x1 v -x1 v x2) → C is satisfied
→ faster than seq but doesn't scale
3-SAT

15. 3-SAT
#thread

16. Mutually Friendly Numbers
#thread