Stop Manual Caching.

Whitepaper - Post-Memoization Development: How Modern Compilers are Automating Performance Optimization

Performance optimization was once a hand-crafted art form. For years, developers manually identified performance bottlenecks and created custom memoization logic to save mere milliseconds of runtime. However, as we enter a world of increasingly complex and heterogeneous software and hardware, manual "tricks" are finally out of gas.

Innovatix Technology Partners offers a comprehensive review of the next generation of high-performance computing. In this white paper, Innovatix examines why the burden of performance is shifting from the developer to the tool chain.

Why Your Current Optimization Approach is Outdated

Although memoization is a basic principle of computer science, applying it on a large-scale within enterprises carries its own unique set of risks:

• Memory Overload: The use of aggressive caching can result in excessive cache thrashing and garbage collection overhead.
• Invalidation Issues: Manually tracking state changes in multi-threaded environments to invalidate cached values represents an opportunity for human error.
• Development Delay: The time spent developing boilerplate caching code detracts from the development of key business logic.

A New Generation: The AI Optimizer

Post-Memoization Development has become the new norm in our industry. Compiler infrastructures powered by LLVM, Profile-Guided Optimization (PGO) and Machine Learning are now capable of optimizing across boundaries which were previously impossible for humans to manage.

Inside this whitepaper you will learn about:

• Global Analysis: How Inter-procedural Optimization (IPO) makes it easier for developers to perform arithmetic operations across their entire application.
• Intelligent Real-World Applications: Why PGO is the largest paradigm shift since the introduction of memoization.
• The Next Great Leap Forward: How Link-Time Optimization (LTO) enables developers to transform the humble "linker" into a powerful optimizer.
• Future of Heuristics: How Reinforcement Learning is currently being applied to help make informed decisions regarding register allocation and in-line functions.

Revising the Role of the Developer

Optimized code is no longer simply about having the most "creative hacks", but rather creating code that provides the best possible information for the compiler to optimize itself.

To learn how to effectively utilize your tool chain in preparation for the post-memoization era, download the full whitepaper.