The Power of Lifetimes

The execution of a program unfolds over some interval of time. The lifetime of every temporary resource (e.g., variable or object) is the time span between that resource’s “creation” and “destruction”. This lifetime is wholly contained within the typically-longer lifetime of the program. The goal of this post is to explore how versatile lifetime analysis has increasingly become in managing memory efficiently, safely and with better performance. By the end of this post, we will explore exciting new ways to apply lifetime analysis, beyond their current support in Rust.

Transitional Permissions

To complete our three-part series on permissions, which began with Race-Safe Strategies, let’s talk about the transitional nature of reference permissions. When are permissions transitional? When we can safely create a copy of a reference which has a different permission than the reference it copied from. There are several ways in which this can happen, which this diagram summarizes (and the following sections explain): The following sections describe the nature of several one-way transitions that flow downward in the diagram.

Interior References and Shared Mutability

In my last post, Race-safe Strategies, one footnote stated “safety issues which look suspiciously similar to race conditions can crop up when a language supports the creation of “interior references” to shared, mutable values of certain types”. Let’s explore that now. I will begin by recapitulating Manish Goregaokar’s excellent post “The Problem With Single-Threaded Shared Mutable”. His post clearly explains why the Rust language wishes to steer developers towards RefCell for shared references over use of Cell, its inflexible shared, mutable counterpart.

Race-Safe Strategies

I recently made the observation that many people seem unaware of the full collection of constraint mechanisms available for protecting race safety. Someone sensibly asked for a link to an article that provides a modern, comprehensive review. It turns out that the pickings are very slim; the best I could find is this Wikipedia article on thread safety. It’s accurate, but incomplete. To close that gap, let me take a stab here at more comprehensive treatment.

Can a compiler guarantee multi-owner memory safety?

Is it possible to improve on Rust’s single-owner strategy to support more complex data structures? Before digging into this challenge, let’s summarize the story so far… The Promise and Limitations of Single-Owner Rust’s single-owner memory management is a form of automatic memory management; a garbage collection strategy that is distinct from tracing and reference-counting. Fundamentally, it is an improvement on RAII, which automatically finalizes some defined resource at the end of its defined lexical scope.

Move Mechanics

Most programming languages support only copy semantics. A value passed to a function or stored in a variable is a copy of the original value. We know it is a copy, because any change we make to the copy has no impact on the original value. A few languages, like C++ and Rust, also support move semantics. Unlike a copy, a transfer moves the original value to its new home; that value is no longer accessible at its previous home.

The Challenge of Counting References

In the world of automatic memory management, reference counting is considered to be one of the easiest to implement. The rules seem simple: When a reference is created to an allocated memory area, set its counter to 1 When the reference is copied (aliased), increment the counter When an alias is destroyed (de-aliased), decrement the counter When the counter reaches zero, free the reference’s memory area The simplicity of these rules does not always translate to a simple implementation.

Data Flow Analysis

The Cone compiler performs a data flow analysis pass after name resolution and type checking. Given that this sort of analysis is rarely covered by compiler literature, I thought it might be useful to jot down some thoughts about its purpose and intriguing mechanics. Goals Like Rust (and unlike C), Cone applies constraints to references that ensure they can only access memory safely, even in the face of concurrency. Some of these constraints are completely enforced by the compiler.

The IR Tree - Introduction

The Cone compiler uses a traditional pipeline to transform source programs into object files. The Intermediate Representation (IR) plays a central role in this design. It is the glue binding together the parser, semantic analysis passes, and the LLVM IR generator. The literature on effective IR design is relatively sparse as compared to other topics, such as parsing, type inference/theory, and optimization techniques. This is a shame. I have devoted far more time trying to get Cone’s IR “right” than I have on any other aspect of the compiler.

Gradual Memory Management

Realtime, quality 3D is punishing on hardware and software alike. At least every 17 milliseconds, the scene needs to be updated and redrawn. Managing memory efficiently across the many large and small data structures that make up an interesting 3D scene is a well-known and important part of that challenge.