Amdahl's Law Calculator
Calculate theoretical speedup in parallel computing and task optimization
Calculate Amdahl's Law Speedup
Percentage of task that can be parallelized
How much faster the parallel part becomes
Time before any improvements
Sequential Part Optimization
How much faster the sequential part becomes
Speedup Analysis
Amdahl's Law Formula
Example Calculation
Video Processing Task
Original time: 120 seconds
Parallelizable: 40% of task
Speedup factor: 4x (using 4 cores)
Result
Speedup: S = 1 / (0.6 + 0.4/4) = 1.43x
New time: 120 / 1.43 = 83.9 seconds
30% improvement
Key Insights
Sequential parts limit overall speedup
Infinite resources can't overcome serial bottlenecks
Focus on parallelizing large portions of work
Optimize sequential parts for better gains
Applications
Understanding Amdahl's Law
What is Amdahl's Law?
Amdahl's Law predicts the theoretical speedup when a portion of a task is improved. It shows that the speedup is limited by the sequential (non-parallelizable) portion of the task, highlighting the importance of optimizing the right parts.
Key Implications
- •Sequential parts create performance bottlenecks
- •Adding more processors has diminishing returns
- •Focus on parallelizing large task portions
- •Sequential optimization can be more effective
Formula Breakdown
Basic Formula
S: Theoretical speedup
p: Proportion parallelized (0-1)
s: Speedup factor of parallel part
Maximum Speedup
Limitations of Amdahl's Law
Assumptions
- • Fixed workload size
- • Perfect parallelization
- • No communication overhead
- • Homogeneous processors
Real-World Factors
- • Memory bandwidth limits
- • Cache coherency overhead
- • Load balancing issues
- • Synchronization costs