Symposium on Code Generation and Optimization 

About: Symposium on Code Generation and Optimization is an academic conference. The conference publishes majorly in the area(s): Compiler & Code generation. Over the lifetime, 561 publications have been published by the conference receiving 25892 citations.

LLVM: a compilation framework for lifelong program analysis & transformation

Abstract: We describe LLVM (low level virtual machine), a compiler framework designed to support transparent, lifelong program analysis and transformation for arbitrary programs, by providing high-level information to compiler transformations at compile-time, link-time, run-time, and in idle time between runs. LLVM defines a common, low-level code representation in static single assignment (SSA) form, with several novel features: a simple, language-independent type-system that exposes the primitives commonly used to implement high-level language features; an instruction for typed address arithmetic; and a simple mechanism that can be used to implement the exception handling features of high-level languages (and setjmp/longjmp in C) uniformly and efficiently. The LLVM compiler framework and code representation together provide a combination of key capabilities that are important for practical, lifelong analysis and transformation of programs. To our knowledge, no existing compilation approach provides all these capabilities. We describe the design of the LLVM representation and compiler framework, and evaluate the design in three ways: (a) the size and effectiveness of the representation, including the type information it provides; (b) compiler performance for several interprocedural problems; and (c) illustrative examples of the benefits LLVM provides for several challenging compiler problems.

SWIFT: Software Implemented Fault Tolerance

Abstract: To improve performance and reduce power, processor designers employ advances that shrink feature sizes, lower voltage levels, reduce noise margins, and increase clock rates. However, these advances make processors more susceptible to transient faults that can affect correctness. While reliable systems typically employ hardware techniques to address soft-errors, software techniques can provide a lower-cost and more flexible alternative. This paper presents a novel, software-only, transient-fault-detection technique, called SWIFT. SWIFT efficiently manages redundancy by reclaiming unused instruction-level resources present during the execution of most programs. SWIFT also provides a high level of protection and performance with an enhanced control-flow checking mechanism. We evaluate an implementation of SWIFT on an Itanium 2 which demonstrates exceptional fault coverage with a reasonable performance cost. Compared to the best known single-threaded approach utilizing an ECC memory system, SWIFT demonstrates a 51% average speedup.

An infrastructure for adaptive dynamic optimization

Abstract: Dynamic optimization is emerging as a promising approach to overcome many of the obstacles of traditional static compilation. But while there are a number of compiler infrastructures for developing static optimizations, there are very few for developing dynamic optimizations. We present a framework for implementing dynamic analyses and optimizations. We provide an interface for building external modules, or clients, for the DynamoRIO dynamic code modification system. This interface abstracts away many low-level details of the DynamoRIO runtime system while exposing a simple and powerful, yet efficient and lightweight API. This is achieved by restricting optimization units to linear streams of code and using adaptive levels of detail for representing instructions. The interface is not restricted to optimization and can be used for instrumentation, profiling, dynamic translation, etc. To demonstrate the usefulness and effectiveness of our framework, we implemented several optimizations. These improve the performance of some applications by as much as 40% relative to native execution. The average speedup relative to base DynamoRIO performance is 12%.

Using Machine Learning to Focus Iterative Optimization

Abstract: Iterative compiler optimization has been shown to outperform static approaches. This, however, is at the cost of large numbers of evaluations of the program. This paper develops a new methodology to reduce this number and hence speed up iterative optimization. It uses predictive modelling from the domain of machine learning to automatically focus search on those areas likely to give greatest performance. This approach is independent of search algorithm, search space or compiler infrastructure and scales gracefully with the compiler optimization space size. Off-line, a training set of programs is iteratively evaluated and the shape of the spaces and program features are modelled. These models are learnt and used to focus the iterative optimization of a new program. We evaluate two learnt models, an independent and Markov model, and evaluate their worth on two embedded platforms, the Texas Instrument C67I3 and the AMD Au1500. We show that such learnt models can speed up iterative search on large spaces by an order of magnitude. This translates into an average speedup of 1.22 on the TI C6713 and 1.27 on the AMD Au1500 in just 2 evaluations.

The Transmeta Code Morphing/spl trade/ Software: using speculation, recovery, and adaptive retranslation to address real-life challenges

Abstract: Transmeta's Crusoe microprocessor is a full, system-level implementation of the x86 architecture, comprising a native VLIW microprocessor with a software layer, the Code Morphing Software (CMS), that combines an interpreter, dynamic binary translator, optimizer, and run-time system. In its general structure, CMS resembles other binary translation systems described in the literature, but it is unique in several respects. The wide range of PC workloads that CMS must handle gracefully in real-life operation, plus the need for full system-level x86 compatibility, expose several issues that have received little or no attention in previous literature, such as exceptions and interrupts, I/O, DMA, and self-modifying code. In this paper we discuss some of the challenges raised by these issues, and present the techniques developed in Crusoe and CMS to meet those challenges. The key to these solutions is the Crusoe paradigm of aggressive speculation, recovery to a consistent x86 state using unique hardware commit-and-rollback support, and adaptive retranslation when exceptions occur too often to be handled efficiently by interpretation.