tcc is a compiler that provides efficient and high-level access to dynamic code generation. It implements the `C ("Tick-C") programming language, an extension of ANSI C that supports dynamic code generation [15]. `C gives power and flexibility in specifying dynamically generated code: whereas most other systems use annotations to denote run-time invariants, `C allows the programmer to specify and compose arbitrary expressions and statements at run time. This degree of control is needed to efficiently implement some of the most important applications of dynamic code generation, such as "just in time" compilers [17] and efficient simulators [10, 48, 46]. The paper focuses on the techniques that allow tcc to provide `C's flexibility and expressiveness without sacrificing run-time code generation efficiency. These techniques include fast register allocation, efficient creation and composition of dynamic code specifications, and link-time analysis to reduce the size of dynamic code generato...

Many parallel programs are written in SPMD style, i.e. by running the same sequential program on all processes. SPMD programs include synchronization, but it is easy to write incorrect synchronization patterns. We propose a system that verifies a program's synchronization pattern. We also propose language features to make the synchronization pattern more explicit and easily checked. We have implemented a prototype of our system for Split-C and successfully verified the synchronization structure of realistic programs. 1 Introduction Explicitly-parallel programming---where the programmer specifies the parallelism in a computation---is arguably the most widely used parallel programming paradigm. Despite many years of practical experience, there has been little work on the static semantics of explicitly-parallel programming languages. We propose a static semantics for global synchronization that guarantees an explicitly parallel program has no global synchronization errors. Our proposal i...

This paper presents dynamic feedback, a technique that enables computations to adapt dynamically to different execution environments. A compiler that uses dynamic feedback produces several different versions of the same source code; each version uses a different optimization policy. The generated code alternately performs sampling phases and production phases. Each sampling phase measures the overhead of each version in the current environment. Each production phase uses the version with the least overhead in the previous sampling phase. The computation periodically resamples to adjust dynamically to changes in the environment.

Compile-time optimization is often limited by a lack of target machine and input data set knowledge. Without this information, compilers may be forced to make conservative assumptions to preserve correctness and to avoid performance degradation. In order to cope with this lack of information at compile-time, adaptive and dynamic systems can be used to perform optimization at runtime when complete knowledge of input and machine parameters is available. This paper presents a compiler-supported high-level adaptive optimization system. Users describe, in a domain specific language, optimizations performed by stand-alone optimization tools and backend compiler flags, as well as heuristics for applying these optimizations dynamically at runtime. The ADAPT compiler reads these descriptions and generates application-specific runtime systems to apply the heuristics. To facilitate the usage of existing tools and compilers, overheads are minimized by decoupling optimization from execution. Our system, ADAPT, supports a range of paradigms proposed recently, including dynamic compilation, parameterization and runtime sampling. We demonstrate our system by applying several optimization techniques to a suite of benchmarks on two target machines. ADAPT is shown to consistently outperform statically generated executables, improving performance by as much as 70%.

Specializing programs with respect to run-time values has been shown to drastically improve code performance on realistic programs ranging from operating systems to graphics. Recently, various approaches to specializing code at run-time have been proposed. However, these approaches still suffer from shortcomings that limit their applicability: they are manual, too expensive, or require programs to be written in a dedicated language. We solve these problems by introducing new techniques to implement run-time specialization. The key to our approach is the use of code templates. Templates are automatically generated from ordinary programs and are optimized before run time, allowing high-quality code to be quickly generated at run time. Experimental results obtained on scientific and graphics code indicate that our approach is highly effective. Little run-time overhead is introduced, since code generation primarily consists of copying instructions. Run-time specialized programs run up to 1...

Designing and implementing generic software components is encouraged by languages such as object-oriented ones and commonly advocated in most application areas. Generic software components have many advantages among which the most important is reusability. However, it comes at a price: genericity often incurs a loss of efficiency. This paper presents an approach aimed at reconciling genericity and efficiency. To do so, we introduce declarations to the Java language to enable a programmer to specify how generic programs should be specialized for a particular usage pattern. Our approach has been implemented as a compiler from our extended language into standard Java. 1 Introduction The object-oriented paradigm has well-recognized advantages for application design, and more specifically for program structure. It makes it possible to decompose an application in terms of well-defined, generic components, closely corresponding to the structure of the modeled problem. This structuring leads...

We describe Vortex, an optimizing compiler intended to produce high-quality code for programs written in a heavily-object-oriented style. To achieve this end, Vortex includes a number of intra- and interprocedural static analyses that can exploit knowledge about the whole program being compiled, including intraprocedural class analysis, class hierarchy analysis, and exhaustive class testing, and profile-guided optimizations such as receiver class prediction and selective specialization. To make whole-program optimization practical, Vortex automatically tracks cross-file optimization dependencies at a fine granularity, triggering selective recompilation of affected compiled files whenever the source program changes. Empirical measurements of five purely object-oriented benchmark programs written in Cecil, ranging in size from several hundred to 75,000 lines of source code, indicate that these optimization techniques improve performance of large programs by more than a factor of three over a system with only intraprocedural static optimizations. Vortex is written in Cecil, and it has been used as its own compiler and optimizer during its development for the past two years. Vortex’s optimizations and implementation techniques should be useful for any language or program where optimizations to reduce the cost of polymorphism are important, including object-oriented languages (we are currently adding front-ends for C++, Modula-3, and Java to Vortex to study its effectiveness on these other language styles) and other highlevel symbolic, functional, and logic languages.

Aggressive program optimization requires accurate profile information, but such accuracy requires many samples to be collected. We explore a novel profiling architecture that reduces the overhead of collecting each sample by including a programmable co-processor that analyzes a stream of profile samples generated by a microprocessor. From this stream of samples, the co-processor can detect correlations between instructions (e.g., memory dependence profiling) as well as those between different dynamic instances of the same instruction (e.g., value profiling). The profiler's programmable nature allows a broad range of data to be extracted, post-processed, and formatted, as well as provides the flexibility to tailor the profiling application to the program under test. Because the co-processor is specialized for profiling, it can execute profiling applications more efficiently than a general-purpose processor. The co-processor should not significantly impact the cost or performance of the ...

The high performance implementation of Java Virtual Machines (JVM) and Just-In-Time (JIT) compilers is directed toward adaptive compilation optimizations on the basis of online runtime profile in-formation. This paper describes the design and implementation of a dynamic optimization framework in a production-level Java JIT compiler. Our approach is to employ a mixed mode interpreter and a three level optimizing compiler, supporting quick, full, and spe-cial optimization, each of which has a different set of tradeoffs be-tween compilation overhead and execution speed. A lightweight sampling profiler operates continuously during the entire program's execution. When necessary, detailed information on runtime behav-ior is collected by dynamically generating instrumentation code which can be installed to and uninstalled from the specified recom-pilation target code. Value profiling with this instrumentation mechanism allows fully automatic code specialization to be per-formed on the basis of specific parameter values or global data at the highest optimization level. The experimental results show that our approach offers high performance and a low code expansion ra-tio in both program startup and steady state measurements in com-parison to the compile-only approach, and that the code specializa-tion can also contribute modest pertbrmance improvements. 1.

Automatic program specialization can derive e#cient implementations from generic components, thus reconciling the often opposing goals of genericity and e#ciency. This technique has proved useful within the domains of imperative, functional, and logical languages, but so far has not been explored within the domain of object-oriented languages.