In today’s world, software plays a crucial role in our daily lives. We can place orders and have groceries delivered to our doorsteps within minutes, and we receive real-time notifications about traffic congestion. In India, with systems like UPI, financial transactions are executed at a rate of than 10K RPS during peak hours
UPI Statistics
Looking at UPI statistics:
In June 2024, 13,885 million transactions were recorded (source: NPCI), which translates to:
Per Day: 462,838,000 transactions
Per Hour: 19,284,916.67 transactions
Per Minute: 321,415.28 transactions
Per Second: 5,356.92 transactions
Performance Expectations
We don’t like to use slow and laggy applications. We want our software to work with a latency of less than 100 ms, delivering the highest throughput and lowest latency with minimal hardware costs for optimum performance.
Importance of parallelism and concurrency
Understanding parallelism and concurrency is crucial in achieving the performance expectations and demands of modern software applications. Here’s why it’s important:
Performance Demands: As highlighted, applications need to handle enormous transaction volumes swiftly. Achieving low latency (less than 100 ms) and high throughput requires efficient utilization of computing resources.
Resource Optimization: Parallelism allows tasks to be divided among multiple processors or cores, leveraging hardware capabilities effectively. Concurrency enables handling multiple tasks simultaneously, enhancing overall system efficiency.
User Experience: Users expect seamless, responsive applications. Efficient use of parallelism and concurrency ensures applications remain responsive even under heavy loads, enhancing user satisfaction.
Cost Efficiency: Optimizing performance through parallelism and concurrency can reduce hardware requirements, minimizing costs while maximizing performance metrics like throughput and latency.
Competitive Advantage: Businesses that deliver fast, reliable software gain a competitive edge. Understanding and implementing parallelism and concurrency can contribute significantly to meeting market demands.
Scalability: Scalable applications can handle growing user bases and increasing transaction volumes without sacrificing performance. Parallel and concurrent programming techniques are fundamental to achieving scalability.
By learning about parallelism and concurrency, we will equip ourself with essential skills to design and develop software that meets these critical performance expectations, contributing to the success and usability of modern applications.
