Add to ORKGAbstract—We present a fully automated approach to project the relative performance of an OpenCL program over different GPUs. Performance projections can be made within a small amount of time, and the projection overhead stays relatively constant with the input data size. As a result, the technique can help runtime tools make dynamic decisions about which GPU would run faster for a given kernel. Usage cases of this technique include scheduling or migrating GPU workloads over a heterogeneous cluster with different types of GPUs. I
The next-generation of supercomputers will feature a diverse mix of accelerator devices. The increas...
Graphics Processing Units (GPUs) have been successfully used to accelerate scientific applications d...
Offloading the most demanding parts of applications to an edge GPU server cluster to save power or i...
General purpose GPU based systems are highly attractive as they give potentially massive performance...
General-purpose GPU-based systems are highly attractive, as they give potentially massive performanc...
Despite the fact that GPU was originally intended to be as a co-processor specializing in graphics r...
Heterogeneous systems consisting of multiple CPUs and GPUs are increasingly attractive as platforms ...
OpenCL (Open Computing Language) is a heterogeneous programming framework for developing application...
Abstract. Heterogeneous computing has become prevalent due to the comput-ing power and low cost of G...
Abstract. Recently, OpenCL, a new open programming standard for GPGPU programming, has become availa...
Heterogeneous multicore architectures with CPU and add-on GPUs or streaming processors are now widel...
Heterogeneous computing systems with multiple CPUs and GPUs are increasingly popular. Today, heterog...
Many computer systems now include both CPUs and programmable GPUs. OpenCL, a new programming framew...
Abstract—The use of GPU clusters for scientific applications in areas such as physics, chemistry and...
Graphic processing units (GPUs) as hardware platforms have been gaining popularity in general purpos...
The next-generation of supercomputers will feature a diverse mix of accelerator devices. The increas...
Graphics Processing Units (GPUs) have been successfully used to accelerate scientific applications d...
Offloading the most demanding parts of applications to an edge GPU server cluster to save power or i...
General purpose GPU based systems are highly attractive as they give potentially massive performance...
General-purpose GPU-based systems are highly attractive, as they give potentially massive performanc...
Despite the fact that GPU was originally intended to be as a co-processor specializing in graphics r...
Heterogeneous systems consisting of multiple CPUs and GPUs are increasingly attractive as platforms ...
OpenCL (Open Computing Language) is a heterogeneous programming framework for developing application...
Abstract. Heterogeneous computing has become prevalent due to the comput-ing power and low cost of G...
Abstract. Recently, OpenCL, a new open programming standard for GPGPU programming, has become availa...
Heterogeneous multicore architectures with CPU and add-on GPUs or streaming processors are now widel...
Heterogeneous computing systems with multiple CPUs and GPUs are increasingly popular. Today, heterog...
Many computer systems now include both CPUs and programmable GPUs. OpenCL, a new programming framew...
Abstract—The use of GPU clusters for scientific applications in areas such as physics, chemistry and...
Graphic processing units (GPUs) as hardware platforms have been gaining popularity in general purpos...
The next-generation of supercomputers will feature a diverse mix of accelerator devices. The increas...
Graphics Processing Units (GPUs) have been successfully used to accelerate scientific applications d...
Offloading the most demanding parts of applications to an edge GPU server cluster to save power or i...