CURD: a dynamic CUDA race detector

Low Complexity Corner Detector Using CUDA for Multimedia Applications

High speed feature detection is a requirement for many real-time multimedia and computer vision applications. In previous work, the Harris and KLT algorithms were redesigned to increase the performance by reducing the algorithmic complexity, resulting in the Low Complexity Corner Detector algorithm. To attain further speedup, this paper proposes the implementation of this low complexity corner ...

Automated Dynamic Analysis of CUDA Programs

Recent increases in the programmability and performance of GPUs have led to a surge of interest in utilizing them for general-purpose computations. Tools such as NVIDIA’s Cuda allow programmers to use a C-like language to code algorithms for execution on the GPU. Unfortunately, parallel programs are prone to subtle correctness and performance bugs, and Cuda tool support for solving these remain...

LDetector: A Low Overhead Race Detector For GPU Programs

Data race detection becomes an important problem in GPU programming. The paper presents a novel solution mainly aimed at detecting data races happening in shared memory accesses with no use of atomic primitives. It makes use of compiler support to privatize shared data and then at run time parallelizes data race checking. It has two distinct features. First, unlike previous existing work, our w...

A new physiologic race

A Practical Dynamic Buffer Overflow Detector

Despite previous efforts in auditing software manually and automatically, buffer overruns are still being discovered in programs in use. A dynamic bounds checker detects buffer overruns in erroneous software before it occurs and thereby prevents attacks from corrupting the integrity of the system. Dynamic buffer overrun detectors have not been adopted widely because they either (1) cannot guard...