Program representation size in an intermediate language with intersection and union types

The CIL compiler for core Standard ML compiles whole programs using a novel typed intermediate language (TIL) with intersection and union types and flow labels on both terms and types. The CIL term representation duplicates portions of the program where intersection types are introduced and union types are eliminated. This duplication makes it easier to represent type information and to introduce customized data representations. However, duplication incurs compile-time space costs that are potentially much greater than are incurred in TILs employing type-level abstraction or quantification. In this paper, we present empirical data on the compile-time space costs of using CIL as an intermediate language. The data shows that these costs can be made tractable by using sufficiently fine-grained flow analyses together with standard hash-consing techniques. The data also suggests that non-duplicating formulations of intersection (and union) types would not achieve significantly better space complexity.National Science Foundation (CCR-9417382, CISE/CCR ESS 9806747); Sun grant (EDUD-7826-990410-US); Faculty Fellowship of the Carroll School of Management, Boston College; U.K. Engineering and Physical Sciences Research Council (GR/L 36963, GR/L 15685

Strongly typed flow-directed representation transformations

closure conversion, inlining Abstract We present a new framework for transforming data representations in a strongly typed intermediate language. Our method allows both value producers (sources) and value consumers (sinks) to support multiple representations, automatically inserting any required code. Specialized representations can be easily chosen for particular source/sink pairs. The framework is based on these techniques: 1. Flow annotated types encode the "flows-from " (source) and "flows-to " (sink) information of a flow graph. 2. Intersection and union types support (a) encoding precise flow information, (b) separating flow information so that transformations can be well typed, (c) automatically reorganizing flow paths to enable multiple representations

Type- and Flow-Directed Compilation for Specialized Data Representations

The combination of intersection and union types with ow types gives the compiler writer unprecedented exibility in choosing data representations in the context of a typed intermediate language. We present the design of such a language and the design of a framework for exploiting the type system to support multiple representations of the same data type in a single program. The framework can transform the input term, in a type-safe way, so that dierent data representations can be used in the transformed term | even if they share a use site in the pre-transformed term. We have implemented a compiler using the typed intermediate language and instantiated the framework to allow specialized function representations. We test the compiler on a set of benchmarks and show that the compile-time performance is reasonable. We further show that the compiled code does indeed bene t from specialized function representations

Functioning without closure: Type-safe customized function representations for Standard ML

The CIL compiler for core Standard ML compiles whole ML programs using a novel typed intermediate language that supports the generation of type-safe customized data representations. In this paper, we present empirical data comparing the relative efficacy of several different flow-based customization strategies for function representations. We develop a cost model to interpret dynamic counts of operations required for each strategy. In this cost model, customizing the representation of closed functions gives a 12–17 % improvement on average over uniform closure representations, depending on the layout of the closure. We also present data on the relative effectiveness of various strategies for reducing representation pollution, i.e., situations where flow constraints require the representation of a value to be less efficient than it would be in ideal circumstances. For the benchmarks tested and the types of representation pollution detected by our compiler, the pollution removal strategies we consider often cost more in overhead than they gain via enabled customizations. Notable exceptions are selective defunctionalization, a function representation strategy that often achieves significant customization benefits via aggressive pollution removal, and a simple form of flow-directed inlining, in which pollution removal allows multiple functions to be inlined at the same call site

Compiling with Polymorphic and Polyvariant Flow Types

Optimizing compilers for function-oriented and object-oriented languages exploit type and flow information for efficient implementation. Although type and flow information (both control and data flow) are inseparably intertwined, compilers usually compute and represent them separately. Partially, this has been a result of the usual polymorphic type systems using 8 and 9 quantifiers, which are difficult to use in combination with flow annotations. In the Church Project, we are experimenting with intermediate languages that integrate type and flow information into a single flow type framework. This integration facilitates the preservation of flow and type information through program transformations. In this paper we describe CIL, an intermediate language supporting polymorphic types and polyvariant flow information and describe its application in program optimiziation. We are experimenting with this intermediate language in a flow and typedirected compiler for a functional language. ..

A Typed Intermediate Language for Flow-Directed Compilation

We present a typed intermediate language # CIL for optimizing compilers for function-oriented and polymorphically typed programming languages (e.g., ML). The language # CIL is a typed lambda calculus with product, sum, intersection, and union types as well as function types annotated with flow labels. A novel formulation of intersection and union types supports encoding flow information in the typed program representation. This flow information can direct optimization

A Calculus with Polymorphic and Polyvariant Flow Types

We present # , a typed #-calculus which serves as the foundation for a typed intermediate language for optimizing compilers for higher-order polymorphic programming languages. The key innovation of # is a novel formulation of intersection and union types and flow labels on both terms and types. These flow types can encode polyvariant control and data flow information within a polymorphically typed program representation. Flow types can guide a compiler in generating customized data representations in a strongly typed setting. Since # enjoys confluence, standardization, and subject reduction properties, it is a valuable tool for reasoning about programs and program transformations

Strongly Typed Flow-Directed Representation Transformations (Extended Abstract)

We present a new framework for transforming data representations in a strongly typed intermediate language. Our method allows both value producers (sources) and value consumers (sinks) to support multiple representations, automatically inserting any required code. Specialized representations can be easily chosen for particular source/sink pairs. The framework is based on these techniques: 1. Flow annotated types encode the "flows-from" (source) and "flows-to" (sink) information of a flow graph. 2. Intersection and union types support (a) encoding precise flow information, (b) separating flow information so that transformations can be well typed, (c) automatically reorganizing flow paths to enable multiple representations. As an instance of our framework, we provide a function representation transformation that encompasses both closure conversion and inlining. Our framework is adaptable to data other than functions