Machine learning and parallel processing are extremely commonly used to enhance computing power to induce knowledge from an outsized volume of data. To deal with the problem of complexity and high ...

In parallel distributed data processing frameworks like Spark and Flink, task scheduling has a great impact on cluster performance. Though task Scheduling has proven to be an NP-complete problem, a ...

Monte Carlo π Calculation - Parallel Programming Project Result: 6.82x speedup on 8-core CPU Domain: Monte Carlo Simulations Approach: Java ExecutorService + LongAdder ...