C++ Performance Optimization and Scaling Strategies
Duration
3 Days (8 hours per day)
Level
Advanced Level
Design and Tailor this course
As per your team needs
This course aims to equip learners with practical skills for optimizing C++ applications’ performance and scalability. There is in-depth focus on topics such as memory management, CPU profiling, and network optimization using performance analysis tools. By the end of the course, participants will be able to design efficient, scalable systems and implement advanced performance tuning techniques, to meet performance standards.
By the end of this course, you will be able to address performance issues in C++ applications by identifying and resolving issues related to memory, CPU, and network. You will gain practical exposure to tools like Valgrind, AddressSanitizer, gperftools, and Wireshark and insights into scaling strategies and best practices for building high-performing real-world applications.
Key Takeaways:
- Proficiency in profiling and optimization tools like Valgrind, gperftools, AddressSanitizer, and Intel VTune.
- Practical methods for detecting and resolving memory leaks.
- Techniques to reduce CPU usage and optimize multi-threaded tasks.
- Best practices for scalable architectures like load balancing and clustering.
- Network optimization using Wireshark and data serialization techniques.
- C++ developers and engineers
- System architects
- DevOps engineers focused on performance tuning
- Overview of Valgrind, gperftools, and perf
- Importance of performance metrics: Memory, CPU, network
- Setting up profiling environments
- Interpreting profiler outputs for actionable insights
- Hands-on Lab: Installing and configuring Valgrind, performing basic memory profiling on a C++ application
- Understanding memory allocation, deallocation, and memory leaks
- Tools: AddressSanitizer and Valgrind’s Memcheck
- Diagnosing and fixing common memory leaks
- Best practices for memory management in C++
- Hands-on Lab: Using AddressSanitizer to identify and resolve memory leaks in a sample C++ application
- Understanding CPU-bound tasks and multi-threading in C++
- Profiling CPU usage with gperftools
- Reducing CPU usage through efficient algorithms
- Managing concurrency for optimal CPU performance
- Hands-on Lab: Profiling a multi-threaded C++ program and optimizing for CPU performance
- Vertical vs. horizontal scaling: Pros and cons
- Load balancing strategies for distributed systems
- Clustering techniques and architecture patterns
- Case studies of scalable C++ systems
- Hands-on Lab: Implementing a load-balanced C++ application using Docker and Kubernetes
- Network packet analysis with Wireshark
- Minimizing network latency and optimizing bandwidth
- Efficient data serialization techniques for network communication
- Best practices for network performance in C++
- Hands-on Lab: Capturing and analyzing network traffic with Wireshark, optimizing a networked C++ application
- Code-level optimizations for CPU and memory
- Using heap analyzers for memory management
- Advanced profiling with Intel VTune
- Reducing binary size and improving execution speed
- Hands-on Lab: Applying advanced tuning techniques to optimize performance in a C++ project
- Strong foundation of intermediate C++ concepts like pointers, templates, and STL
- Exposure to Linux environments and command-line tools
- Knowledge of multi-threading and concurrent programming in C++
- Exposure to network programming basics (optional)