In this paper, we present our implementation of an Auto tuning system, written in C++, which incorporate the use of OpenCL kernels. We deploy this approach on different GPU architectures, evaluating the performance of the approach. Our main focus is to easily generate tuned code, that would otherwise require a large amount of empirical testing, and then run it on any kind of device. This is achieved through the auto tuning framework, which will create different kernels, compile and run them on the device and output the best performing kernel on the given platform.BLAS is much used in performance critical applications, and is a good candidate for execution on GPUs due to its potential performance increase. Our implementation was benchmarked ...
Graphics Processing Units (GPUs) have revolutionized the computing landscape over the past decades. ...
In high-performance computing, excellent node-level performance is required for the efficient use of...
Writing high performance GPGPU code is often difficult and time-consuming, potentially requiring lab...
Graphics Processing Units (GPUs) have revolutionized the HPC landscape. The first generation of exas...
Graphics Processing Units (GPUs) have revolutionized the HPC landscape. The first generation of exas...
Graphics Processing Units (GPUs) have revolutionized the computing landscape in the past decade and ...
Graphics Processing Units (GPUs) have revolutionized the HPC landscape. The first generation of exas...
Recent years have witnessed phenomenal growth in the application, and capabilities of Graphical Proc...
In this work, we evaluate OpenCL as a programming tool for developing performance-portable applicati...
The continuing evolution of Graphics Processing Units (GPU) has shown rapid performance increases ov...
We present a novel strategy for automatic performance tuning of GPU programs. The strategy combines ...
The focus of this work is the automatic performance tuning of stencil computations on Graphics Proce...
We have developed several autotuning benchmarks in CUDA that take into account performance-relevant ...
Abstract. Autotuning is an established technique for adjusting perfor-mance-critical parameters of a...
Optimal performance is an important goal in compute intensive applications. For GPU applications, th...
Graphics Processing Units (GPUs) have revolutionized the computing landscape over the past decades. ...
In high-performance computing, excellent node-level performance is required for the efficient use of...
Writing high performance GPGPU code is often difficult and time-consuming, potentially requiring lab...
Graphics Processing Units (GPUs) have revolutionized the HPC landscape. The first generation of exas...
Graphics Processing Units (GPUs) have revolutionized the HPC landscape. The first generation of exas...
Graphics Processing Units (GPUs) have revolutionized the computing landscape in the past decade and ...
Graphics Processing Units (GPUs) have revolutionized the HPC landscape. The first generation of exas...
Recent years have witnessed phenomenal growth in the application, and capabilities of Graphical Proc...
In this work, we evaluate OpenCL as a programming tool for developing performance-portable applicati...
The continuing evolution of Graphics Processing Units (GPU) has shown rapid performance increases ov...
We present a novel strategy for automatic performance tuning of GPU programs. The strategy combines ...
The focus of this work is the automatic performance tuning of stencil computations on Graphics Proce...
We have developed several autotuning benchmarks in CUDA that take into account performance-relevant ...
Abstract. Autotuning is an established technique for adjusting perfor-mance-critical parameters of a...
Optimal performance is an important goal in compute intensive applications. For GPU applications, th...
Graphics Processing Units (GPUs) have revolutionized the computing landscape over the past decades. ...
In high-performance computing, excellent node-level performance is required for the efficient use of...
Writing high performance GPGPU code is often difficult and time-consuming, potentially requiring lab...