Compiling Irregular Software to Specialized Hardware

High-level synthesis (HLS) has simplified the design process for energy-efficient hardware accelerators: a designer specifies an accelerator’s behavior in a “high-level” language, and a toolchain synthesizes register-transfer level (RTL) code from this specification. Many HLS systems produce efficient hardware designs for regular algorithms (i.e., those with limited conditionals or regular memory access patterns), but most struggle with irregular algorithms that rely on dynamic, data-dependent memory access patterns (e.g., traversing pointer-based structures like lists, trees, or graphs). HLS tools typically provide imperative, side-effectful languages to the designer, which makes it difficult to correctly specify and optimize complex, memory-bound applications. In this dissertation, I present an alternative HLS methodology that leverages properties of functional languages to synthesize hardware for irregular algorithms. The main contribution is an optimizing compiler that translates pure functional programs into modular, parallel dataflow networks in hardware. I give an overview of this compiler, explain how its source and target together enable parallelism in the face of irregularity, and present two specific optimizations that further exploit this parallelism. Taken together, this dissertation verifies my thesis that pure functional programs exhibiting irregular memory access patterns can be compiled into specialized hardware and optimized for parallelism. This work extends the scope of modern HLS toolchains. By relying on properties of pure functional languages, our compiler can synthesize hardware from programs containing constructs that commercial HLS tools prohibit, e.g., recursive functions and dynamic memory allocation. Hardware designers may thus use our compiler in conjunction with existing HLS systems to accelerate a wider class of algorithms than before

Generic Constraints for Type-Safe Embedded Programming

Domain-specific languages (DSLs) are everywhere, with applications in areas such as parser generation, music synthesis, parallel programming and even the design of domain-specific languages. However, while the pay-off in using a DSL may be substantial, the cost of introducing a language may be made prohibitively high by the need to construct a supporting toolchain. A common tactic is to embed a DSL into a general-purpose host programming language. Existing infrastructure such as a language’s compiler or type system may be re-used, provided that the embedding accurately captures the properties of the DSL. While the rich type systems and orthogonal abstraction features of modern functional languages have proved particularly capable in this regard, they are not without their shortcomings. Building type-safe functions defined over an embedded DSL can introduce application-specific type constraints that end up being imposed on the DSL data types themselves. At best, these constraints are unwieldy and at worst they can limit the range of DSL expressions that can be built. In this thesis we tackle the problem of accurately embedding a DSL’s type system into that of the purely functional language Haskell. We present a framework for expressing application-specific constraints at the point of a DSL expression’s use rather than when the DSL’s embedding is defined. We show how our framework can be applied more generally to capture arbitrary properties of a DSL expression and, in certain cases, how we may subsequently prove additional safety properties such as the totality of a function which operates over DSL expressions. We evaluate our techniques by illustrating their use in constructing a DSL for heterogeneous parallel programming. However, our methods have potentially wider applications such as context-dependent computation, which are also discussed

HERMIT: Mechanized Reasoning during Compilation in the Glasgow Haskell Compiler

It is difficult to write programs which are both correct and fast. A promising approach, functional programming, is based on the idea of using pure, mathematical functions to construct programs. With effort, it is possible to establish a connection between a specification written in a functional language, which has been proven correct, and a fast implementation, via program transformation. When practiced in the functional programming community, this style of reasoning is still typically performed by hand, by either modifying the source code or using pen-and-paper. Unfortunately, performing such semi-formal reasoning by directly modifying the source code often obfuscates the program, and pen-and-paper reasoning becomes outdated as the program changes over time. Even so, this semi-formal reasoning prevails because formal reasoning is time-consuming, and requires considerable expertise. Formal reasoning tools often only work for a subset of the target language, or require programs to be implemented in a custom language for reasoning. This dissertation investigates a solution, called HERMIT, which mechanizes reasoning during compilation. HERMIT can be used to prove properties about programs written in the Haskell functional programming language, or transform them to improve their performance. Reasoning in HERMIT proceeds in a style familiar to practitioners of pen-and-paper reasoning, and mechanization allows these techniques to be applied to real-world programs with greater confidence. HERMIT can also re-check recorded reasoning steps on subsequent compilations, enforcing a connection with the program as the program is developed. HERMIT is the first system capable of directly reasoning about the full Haskell language. The design and implementation of HERMIT, motivated both by typical reasoning tasks and HERMIT's place in the Haskell ecosystem, is presented in detail. Three case studies investigate HERMIT's capability to reason in practice. These case studies demonstrate that semi-formal reasoning with HERMIT lowers the barrier to writing programs which are both correct and fast