Accelerators. When you click on or move your mouse over an Accelerator in Internet Explorer, any of the following may be sent to the applicable service provider (which may not be Microsoft): the title and full web address or URL of the current webpage, standard computer information, and any content you have selected. For more information, see xx.xxxxxxxxx.xxx/xxxxxx/?xxxxxx=000000.
Accelerators. When you click on or move your mouse over an Accelera tor in Internet Explorer, any of the following may be sent to the applica ble service provider (which may not be Microsoft): the title and full web address or URL of the current webpage, standard computer information, and any content you have selected. For more information, see xx.xxxxxxxxx.xxx/xxxxxx/?xxxxxx=000000.
Accelerators. When you click on or move your mouse over an Accelera tor in Internet Explorer, any of the following may be sent to the applicable service provider (which may not be Microsoft): the title and full web address or URL of the current webpage, standard computer information, and any content you have selected. For more information, see xx.xxxxxxxxx.xxx/xxxxxx/?XxxxXx=000000.
Accelerators. Accelerators come in a variety of types, from GPGPUs (general purpose graphics processing units) to the Intel Xeon Phi. Accelerators can be used as a standalone item, with increasing numbers of personal computing facilities including programmable GPUs, or attached in small or large numbers to the massively parallel architectures of supercomputers. For specific computational problems, accelerators enable better performances than standard CPU at a lower energy usage (e.g. floating point operations/Watt). To achieve a high level of performance requires a specialised parallelism to expose the required level of vectorisation in the software. With some codes it may be impossible to expose the required level of vectorisation to benefit from using accelerators because the algorithm does not have a high enough level of operational intensity (i.e. enough floating point operations for each memory access). In addition to exposing parallelism, some accelerators (e.g. GPUs), require the use of additional programming techniques in the software (e.g. a new language such as CUDA, or a new API such as OpenCL). Cloud computing Cloud computing enables on-demand access to resources, without the overhead of their ownership. Cloud computing presents the required computational resources to the user by the use of one or more virtual machines. However, this can have a negative impact on performance, depending on the particular problem under consideration. Although virtualisation is now a minimal overhead, due to the use of multiple virtual machines, communication latency in cloud computing is higher than in a dedicated HPC resource, resulting in reduced performance. The use of virtual machines means that the software is not running natively on the hardware and therefore communication is not tightly coupled. However, the performance gap is closing, as cloud service providers adopt hardware capable of the performance of HPC, such as Azure where the interconnect now uses Infiniband, a networking standard commonly used in HPC system. Therefore, if an application has tightly coupled processes, requiring significant communication, cloud computing is likely to perform less well than dedicated supercomputing facilities.
