A. Aiken & D. Gay (1998):
Barrier Inference.
In: Procs. of the Symp. on Principles of Programming Languages (POPL),
pp. 342–354,
doi:10.1145/268946.268974.
M. Boyer, K. Skadron & W. Weimer (2008):
Automated Dynamic Analysis of CUDA Programs.
In: Proc. of the 3rd Workshop on Software Tools for Multicore Systems.
C. Ellison & G. Rosu (2012):
An Executable Formal Semantics of C with Applications.
In: Proc. of the Symp. on Principles of Programming Languages (POPL),
doi:10.1145/2103656.2103719.
C. M. Ellison (2012):
A Formal Semantics of C with Applications.
UIUC.
A. Habermaier (2011):
The Model of Computation of CUDA and Its Formal Semantics.
Technical Report.
Universität Augsburg.
A. Habermaier & A. Knapp (2012):
On the Correctness of the SIMT Execution Model of GPUs.
In: Proc. of the European Symp. on Programming (ESOP),
doi:10.1007/978-3-642-28869-2_16.
M. Harris:
Optimizing Parallel Reduction in CUDA.
In: GPU Technology Conf..
NVIDIA.
G. Li, P. Li, G. Sawaya, G. Gopalakrishnan, I. Ghosh & S. P. Rajan (2012):
GKLEE: Concolic Verification and Test Generation for GPUs.
In: Proc. of the Symp. on Principles and Practices of Parallel Prog. (PPoPP),
doi:10.1145/2145816.2145844.
G. Rosu & T. F. Serbănută (2010):
An Overview of the K Semantic Framework.
Journal of Logic and Algebraic Programming 79(6),
pp. 397–434,
doi:10.1016/j.jlap.2010.03.012.
G. Rosu & A. Stefănescu (2012):
Checking Reachability using Matching Logic.
In: Proc. of the Conf. on Object-Oriented Programming, Systems, Languages, and Applications (OOPSLA),
doi:10.1145/2384616.2384656.
S. Ryoo, C. I. Rodrigues, S. S. Baghsorkhi, S. S. Stone, D. B. Kirk & W. W. Hwu (2008):
Optimization Principles and Application Performance Evaluation of a Multithreaded GPU Using CUDA.
In: Proc. of the Symp. on Principles and Practice of Parallel Prog. (PPoPP),
pp. 73–82,
doi:10.1145/1345206.1345220.
S. Tripakis, C. Stergiou & R. Lublinerman (2010):
Checking Non-Interference in SPMD Programs.
In: Proc. of the 2nd USENIX Workshop on Hot Topics in Parallelism (HotPar),
pp. 1–6.
M. Zheng, V. T. Ravi, F. Qin & G. Agrawal (2011):
GRace: A Low-Overhead Mechanism for Detecting Data Races in GPU Programs.
In: Proc. of the Symp. on Principles and Practice of Parallel Prog. (PPoPP),
doi:10.1145/1941553.1941574.