Efficient detection of determinacy races in Cilk programs
Proceedings of the ninth annual ACM symposium on Parallel algorithms and architectures
POPL '98 Proceedings of the 25th ACM SIGPLAN-SIGACT symposium on Principles of programming languages
Type-based race detection for Java
PLDI '00 Proceedings of the ACM SIGPLAN 2000 conference on Programming language design and implementation
Optimizing compilers for modern architectures: a dependence-based approach
Optimizing compilers for modern architectures: a dependence-based approach
Principles of Program Analysis
Principles of Program Analysis
Reducing Model Checking of the Many to the Few
CADE-17 Proceedings of the 17th International Conference on Automated Deduction
Dynamic partial-order reduction for model checking software
Proceedings of the 32nd ACM SIGPLAN-SIGACT symposium on Principles of programming languages
DySy: dynamic symbolic execution for invariant inference
Proceedings of the 30th international conference on Software engineering
SPEED: Symbolic Complexity Bound Analysis
CAV '09 Proceedings of the 21st International Conference on Computer Aided Verification
Static and Precise Detection of Concurrency Errors in Systems Code Using SMT Solvers
CAV '09 Proceedings of the 21st International Conference on Computer Aided Verification
FLAVERS: a finite state verification technique for software systems
IBM Systems Journal
A symbolic verifier for CUDA programs
Proceedings of the 15th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming
Programming Massively Parallel Processors: A Hands-on Approach
Programming Massively Parallel Processors: A Hands-on Approach
Formal specification of MPI 2.0: Case study in specifying a practical concurrent programming API
Science of Computer Programming
Top ten ways to make formal methods for HPC practical
Proceedings of the FSE/SDP workshop on Future of software engineering research
GRace: a low-overhead mechanism for detecting data races in GPU programs
Proceedings of the 16th ACM symposium on Principles and practice of parallel programming
KLOVER: a symbolic execution and automatic test generation tool for C++ programs
CAV'11 Proceedings of the 23rd international conference on Computer aided verification
GKLEE: concolic verification and test generation for GPUs
Proceedings of the 17th ACM SIGPLAN symposium on Principles and Practice of Parallel Programming
Verifying GPU kernels by test amplification
Proceedings of the 33rd ACM SIGPLAN conference on Programming Language Design and Implementation
A static analysis tool using a three-step approach for data races in HPC programs
Proceedings of the 2012 Workshop on Parallel and Distributed Systems: Testing, Analysis, and Debugging
GPUVerify: a verifier for GPU kernels
Proceedings of the ACM international conference on Object oriented programming systems languages and applications
Parametric flows: automated behavior equivalencing for symbolic analysis of races in CUDA programs
SC '12 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
Symbolic testing of OpenCL code
HVC'11 Proceedings of the 7th international Haifa Verification conference on Hardware and Software: verification and testing
Interleaving and lock-step semantics for analysis and verification of GPU kernels
ESOP'13 Proceedings of the 22nd European conference on Programming Languages and Systems
GPUDet: a deterministic GPU architecture
Proceedings of the eighteenth international conference on Architectural support for programming languages and operating systems
Barrier invariants: a shared state abstraction for the analysis of data-dependent GPU kernels
Proceedings of the 2013 ACM SIGPLAN international conference on Object oriented programming systems languages & applications
A sound and complete abstraction for reasoning about parallel prefix sums
Proceedings of the 41st ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages
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Interest in Graphical Processing Units (GPUs) is skyrocketing due to their potential to yield spectacular performance on many important computing applications. Unfortunately, writing such efficient GPU kernels requires painstaking manual optimization effort which is very error prone. We contribute the first comprehensive symbolic verifier for kernels written in CUDA C. Called the 'Prover of User GPU programs (PUG),' our tool efficiently and automatically analyzes real-world kernels using Satisfiability Modulo Theories (SMT) tools, detecting bugs such as data races, incorrectly synchronized barriers, bank conflicts, and wrong results. PUG's innovative ideas include a novel approach to symbolically encode thread interleavings, exact analysis for correct barrier placement, special methods for avoiding interleaving generation, dividing up the analysis over barrier intervals, and handling loops through three approaches: loop normalization, overapproximation, and invariant finding. PUG has analyzed over a hundred CUDA kernels from public distributions and in-house projects, finding bugs as well as subtle undocumented assumptions.