Task (computing)

About: Task (computing) is a research topic. Over the lifetime, 9718 publications have been published within this topic receiving 129364 citations.

Recommending actions based on context

Abstract: A system creates filters and provides tasks based on a geographic location associated with each task. The geographic location may be in one of several types of coordinate formats, and determined by the actual user location when the task is created of input associated with a desired location. When a user requests tasks for a specified geographic location, the user's tasks are filtered by a particular geographic location associated with the request. The filter may allow tasks that match the location and are within a threshold distance of the location. Tasks having a geographical location that are outside the threshold distance from the location are not provided. When managing tasks from a mobile device, the geographic location can be automatically determined by the mobile device. When managing tasks from a non-mobile device, the geographical location may be received or derived from user input.

Reliable computing with a many-core processor

Abstract: According to embodiments of the disclosed subject matter, cores in a many-core processor may be periodically tested to obtain and/or refresh their dynamic profiles. The dynamic profile of a core may include information on its maximum operating frequency, power consumption, power leakage, functional correctness, and other parameters, as well as the trending information of these parameters. Once a dynamic profile has been created for each core, cores in a many-core processor may be grouped into different bins according to their characteristics. Based on dynamic profiles and the grouping information, the operating system ('OS') or other software may allocate a task to those cores that are most suitable for the task. The interconnect fabric in the many-core processor may be reconfigured to ensure a high level of connectivity among the selected cores. Additionally, cores may be re-allocated and/or re-balanced to a task in response to changes in the environment.

GroupBar: The TaskBar Evolved

Abstract: Our studies have shown that as displays become larger, users leave more windows open for easy multitasking. A larger number of windows, however, may increase the time that users spend arranging and switching between tasks. We introduce GroupBar, a task management system for dealing with the profusion of windows on the PC desktop. Designed to offer the same basic form and function as the existing Microsoft WindowsTM TaskBar, GroupBar additionally allows users to group windows into higher-level tasks and enables task switching with a single mouse click. In order to gain experience with GroupBar usage and to develop reasonable task definitions we conducted a longitudinal field study. Based on the results of that field study, we conducted a comparative user study wherein we found that participants were able to multitask faster when using GroupBar than when using the existing Windows TaskBar.

Secured transaction system and method

Abstract: Systems and methods for performing financial transactions are provided. In one embodiment, the invention provides for method for bank card transactions, including: reading the token information at the point of swipe for traditional and non-traditional POS platforms; performing a low-security task on the token information using a first microprocessor, wherein the non-security task includes one or more tasks from the group of encryption determination, encryption-decryption request, key management, token information delivery, or transactional data delivery; and performing a security-related task on the token information using a second microprocessor based on a request from the first microprocessor, wherein the security-related task includes one or more tasks from the group of token information authentication, token information decryption, or token information encryption. Formatting the encrypted information such that it is compatible with the format of the current POS system.

Adaptive parallelism and Piranha

Abstract: Desktop computers are idle much of the time. Ongoing trends make aggregate LAN "waste"-idle compute cycles-an increasingly attractive target for recycling. Piranha, a software implementation of adaptive parallelism, allows these waste cycles to be recaptured by putting them to work running parallel applications. Most parallel processing is static: programs execute on a fixed set of processors throughout a computation. Adaptive parallelism allows for dynamic processor sets which means that the number of processors working on a computation may vary, depending on availability. With adaptive parallelism, instead of parceling out jobs to idle workstations, a single job is distributed over many workstations. Adaptive parallelism is potentially valuable on dedicated multiprocessors as well, particularly on massively parallel processors. One key Piranha advantage is that task descriptors, not processes, are the basic movable, remappable computation unit. The task descriptor approach supports strong heterogeneity. A process image representing a task in mid computation can't be moved to a machine of a different type, but a task descriptor can be. Thus, a task begun on a Sun computer can be completed by an IBM machine. The authors show that adaptive parallelism has the potential to integrate heterogeneous platforms seamlessly into a unified computing resource and to permit more efficient sharing of traditional parallel processors than is possible with current systems. >