The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In the past, Graphics Processing Unities (GPUs) were mainly used for graphics rendering. In the past 10 years, they have been redesigned and are used to accelerate a wide range of applications, including deep neural networks, image reconstruction and cryptographic algorithms. Despite being the accelerator of choice in a number of important application domains, today’s GPUs receive little attention...
Graphics Processing Units (GPUs) can easily outperform CPUs in processing large-scale data parallel workloads, but are considered weak in processing serialized tasks and communicating with other devices. Pursuing a CPU-GPU collaborative computing model which takes advantage of both devices could provide an important breakthrough in realizing the full performance potential of heterogeneous computing...
Heterogeneous systems, that marry CPUs and GPUs together in a range of configurations, are quickly becoming the design paradigm for today's platforms because of their impressive parallel processing capabilities. However, in many existing heterogeneous systems, the GPU is only treated as an accelerator by the CPU, working as a slave to the CPU master. But recently we are starting to see the introduction...
Graphics Processing Units (GPUs) have been used to run a range of cryptographic algorithms. The main reason to choose a GPU is to accelerate the encryption/decryption speed. Since GPUs are mainly used for graphics rendering, and only recently have they become a fully-programmable parallel computing device, there has been little attention paid to their vulnerability to side-channel attacks. In this...
Floating-point arithmetic is widely used in scientific computing. While many programmers are subliminally aware that floating-point numbers only approximate the reals, few are cognizant of the dangers this entails for programming. Such dangers range from tolerable rounding errors in sequential programs, to unexpected, divergent control flow in parallel code. To address these problems, we present a...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.