A new approach to debugging optimized code
PLDI '92 Proceedings of the ACM SIGPLAN 1992 conference on Programming language design and implementation
A framework for reducing the cost of instrumented code
Proceedings of the ACM SIGPLAN 2001 conference on Programming language design and implementation
Dynamic hot data stream prefetching for general-purpose programs
PLDI '02 Proceedings of the ACM SIGPLAN 2002 Conference on Programming language design and implementation
Loop Transformations for Restructuring Compilers: The Foundations
Loop Transformations for Restructuring Compilers: The Foundations
An updated set of basic linear algebra subprograms (BLAS)
ACM Transactions on Mathematical Software (TOMS)
Loop-Level Parallelism in Numeric and Symbolic Programs
IEEE Transactions on Parallel and Distributed Systems
SPEComp: A New Benchmark Suite for Measuring Parallel Computer Performance
WOMPAT '01 Proceedings of the International Workshop on OpenMP Applications and Tools: OpenMP Shared Memory Parallel Programming
FULLDOC: A Full Reporting Debugger for Optimized Code
SAS '00 Proceedings of the 7th International Symposium on Static Analysis
Low-overhead memory leak detection using adaptive statistical profiling
ASPLOS XI Proceedings of the 11th international conference on Architectural support for programming languages and operating systems
Code Generation in the Polyhedral Model Is Easier Than You Think
Proceedings of the 13th International Conference on Parallel Architectures and Compilation Techniques
Pin: building customized program analysis tools with dynamic instrumentation
Proceedings of the 2005 ACM SIGPLAN conference on Programming language design and implementation
A framework for adaptive algorithm selection in STAPL
Proceedings of the tenth ACM SIGPLAN symposium on Principles and practice of parallel programming
Subroutine profiling results for the CPU2006 benchmarks
ACM SIGARCH Computer Architecture News
A practical automatic polyhedral parallelizer and locality optimizer
Proceedings of the 2008 ACM SIGPLAN conference on Programming language design and implementation
PetaBricks: a language and compiler for algorithmic choice
Proceedings of the 2009 ACM SIGPLAN conference on Programming language design and implementation
LiteRace: effective sampling for lightweight data-race detection
Proceedings of the 2009 ACM SIGPLAN conference on Programming language design and implementation
Alchemist: A Transparent Dependence Distance Profiling Infrastructure
Proceedings of the 7th annual IEEE/ACM International Symposium on Code Generation and Optimization
Scenario Based Optimization: A Framework for Statically Enabling Online Optimizations
Proceedings of the 7th annual IEEE/ACM International Symposium on Code Generation and Optimization
Transparent Debugging of Dynamically Optimized Code
Proceedings of the 7th annual IEEE/ACM International Symposium on Code Generation and Optimization
SD3: A Scalable Approach to Dynamic Data-Dependence Profiling
MICRO '43 Proceedings of the 2010 43rd Annual IEEE/ACM International Symposium on Microarchitecture
Adaptive runtime selection of parallel schedules in the polytope model
Proceedings of the 19th High Performance Computing Symposia
Noise-based testing and analysis of multi-threaded C/C++ programs on the binary level
Proceedings of the 2012 Workshop on Parallel and Distributed Systems: Testing, Analysis, and Debugging
Online dynamic dependence analysis for speculative polyhedral parallelization
Euro-Par'13 Proceedings of the 19th international conference on Parallel Processing
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VMAD (Virtual Machine for Advanced Dynamic analysis) is a platform for advanced profiling and analysis of programs, consisting in a static component and a runtime system. The runtime system is organized as a set of decoupled modules, dedicated to specific instrumenting or optimizing operations, dynamically loaded when required. The program binary files handled by VMAD are previously processed at compile time to include all necessary data, instrumentation instructions and callbacks to the runtime system. For this purpose, the LLVM compiler has been extended to automatically generate multiple versions of the code, each of them tailored for the targeted instrumentation or optimization strategies. The compiler chooses the most suitable intermediate representation for each version, depending on the information to be acquired and on the optimizations to be applied. The control flow graph is adapted to include the new versions and to transfer the control to and from the runtime system, which is in charge of the execution flow orchestration. The strength of our system resides in its extensibility, as one can add support for various new profiling or optimization strategies, independently of the existing modules. VMAD's potential is illustrated by presenting several analysis and optimization applications dedicated to loop nests: instrumentation by sampling, dynamic dependence analysis, adaptive version selection.