2025-12-05 14:34:27

1. Description

This report analyzes the performance of the parallel sum benchmark for different array sizes (N) and levels of task parallelism. We compare computation and communication times and evaluate how execution time and speedup evolve with increasing workloads.

1.1. Session

  • Hostname: feelpp1

  • User: chabannes

  • Time Start: 20251205T143430+0100

  • Time End: 20251205T143518+0100

1.2. Cases

  • Total: 12

  • Failures: 0

  • Runs: 1

2. Parametrization

Hash tasks elements Total Time (s)

pass

a2b76237

1.0

100000000.0

1.5364103317260742

Logs

pass

a2b76237

1.0

100000000.0

1.5364103317260742

Logs

pass

9acbf120

1.0

400000000.0

4.803107500076294

Logs

pass

9acbf120

1.0

400000000.0

4.803107500076294

Logs

pass

595650fc

1.0

700000000.0

7.97005558013916

Logs

pass

595650fc

1.0

700000000.0

7.97005558013916

Logs

pass

edfa2e8b

1.0

1000000000.0

10.993201732635498

Logs

pass

edfa2e8b

1.0

1000000000.0

10.993201732635498

Logs

pass

1987311b

2.0

100000000.0

1.2174618244171143

Logs

pass

1987311b

2.0

100000000.0

1.2174618244171143

Logs

pass

7cb1e44f

2.0

400000000.0

2.7819597721099854

Logs

pass

7cb1e44f

2.0

400000000.0

2.7819597721099854

Logs

pass

eacb935f

2.0

700000000.0

4.026050090789795

Logs

pass

eacb935f

2.0

700000000.0

4.026050090789795

Logs

pass

4265e337

2.0

1000000000.0

5.708710193634033

Logs

pass

4265e337

2.0

1000000000.0

5.708710193634033

Logs

pass

8907778f

4.0

100000000.0

0.9598414897918701

Logs

pass

8907778f

4.0

100000000.0

0.9598414897918701

Logs

pass

821b1f99

4.0

400000000.0

1.5221059322357178

Logs

pass

821b1f99

4.0

400000000.0

1.5221059322357178

Logs

pass

e6be5145

4.0

700000000.0

2.2903292179107666

Logs

pass

e6be5145

4.0

700000000.0

2.2903292179107666

Logs

pass

9929e60c

4.0

1000000000.0

3.3535962104797363

Logs

pass

9929e60c

4.0

1000000000.0

3.3535962104797363

Logs

3. Performance Analysis

3.1. Execution Time vs Number of Tasks

This plot shows the execution time breakdown as the number of tasks increases. It highlights parallel scaling behavior for different array sizes.

3.2. Execution Time vs Problem Size (N)

This plot illustrates how execution time scales with array size N under different task counts. It helps identify compute bottlenecks and memory throughput constraints.

3.3. Speedup Analysis

This speedup plot shows how effectively the computation accelerates when increasing task parallelism. It highlights the scaling behavior of the parallel sum benchmark.