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.
Hardware scaling and low-power considerations associated with the quest for exascale and extreme scale computing are driving system designers to consider new runtime and execution models such as the event-driven-task (EDT) models that enable more concurrency and reduce the amount of synchronization. Further, for performance, productivity, and code sustainability reasons, there is an increasing demand...
The Open Community Runtime (OCR) is a new runtime system designed to meet the needs of extreme-scale computing. While there is growing support for the idea that future execution models will be based on dynamic tasks, there is little agreement on what else should be included. OCR minimally adds events for synchronization and relocatable data-blocks for data management to form a complete system that...
In the last decade, the scope of software optimizations expanded to encompass energy consumption on top of the classical runtime minimization objective. In that context, several optimizations have been developed to improve the software energy efficiency. However, these optimizations commonly rely on long profiling steps and are often implemented as unstable runtime systems, which limits their applicability...
Computers across the board, from embedded to future exascale computers, are consistently designed with deeper memory hierarchies. While this opens up exciting opportunities for improving software performance and energy efficiency, it also makes it increasingly difficult to efficiently exploit the hardware. Advanced compilation techniques are a possible solution to this difficult problem and, among...
Writing high performance software requires the programmer to take advantage of multi-core processing. This can be done through tools like OpenMP, which allow the programmer to mark parallel loops. Identifying parallelizable loops, however, is a non-trivial task. Furthermore, transformations can be applied to a loop nest to expose parallelism. Polyhedral compilation has become an increasingly popular...
Taking advantage of multi-core processing has become crucial in realizing significant performance gains for most applications. When it comes to performance optimization, this has led to a delicate balancing act between parallelism and locality. Furthermore, exposing parallelism can require some non-trivial transformations. Although tools exist to automatically identify good transformations, a user...
A significant source for enhancing application performance and for reducing power consumption in embedded processor applications is to improve the usage of the memory hierarchy. Such objective classically translates into optimizing spatial and temporal data locality especially for nested loops. In this paper, we focus on temporal data locality. Unlike many existing methods, our approach pays special...
This paper presents a new method for computing the integer hull of a parameterized rational polyhedron by introducing the concept of periodic polyhedron. Besides concerning generally parametric combinatorial optimization, the method has many applications for the analysis, optimization and parallelization of loop nests, especially in compilers.
The technology scaling has initiated two distinct trends that are likely to continue into future: first, the increased parallelism in hardware and second, the increasing performance and energy cost of communication relative to computation. Both of the above trends call for development of compiler and runtime systems to automatically parallelize programs and reduce communication in parallel computations...
For applications that deal with large amounts of high dimensional multi-aspect data, it is natural to represent such data as tensors or multi-way arrays. Tensor computations, such as tensor decompositions, are increasingly being used to extract and explain properties of such data. An important class of tensors is the symmetric tensor, which shows up in real-world applications such as signal processing,...
Existing high-level, source-to-source compilers can accept input programs in a high-level language (e.g., C) and perform complex automatic parallelization and other mappings using various optimizations. These optimizations often require trade-offs and can benefit from the user's involvement in the process. However, because of the inherent complexity, the barrier to entry for new users of these high-level...
With Exascale performance and its challenges in mind, one ubiquitous concern among architects is energy efficiency. Petascale systems projected to Exascale systems are unsustainable at current power consumption rates. One major contributor to system-wide power consumption is the number of memory operations leading to data movement and management techniques applied by the runtime system. To address...
Irregular computations over large-scale sparse data are prevalent in critical data applications and they have significant room for improvement on modern computer systems from the aspects of parallelism and data locality. We introduce new techniques to efficiently map large irregular computations onto modern multi-core systems with non-uniform memory access (NUMA) behavior. Our techniques are broadly...
As distributed memory systems grow larger, communication demands have increased. Unfortunately, while the costs of arithmetic operations continue to decrease rapidly, communication costs have not. As a result, there has been a growing interest in communication-avoiding algorithms for some of the classic problems in numerical computing, including communication-avoiding Fast Fourier Transforms (FFTs)...
DARPA's Ubiquitous High-Performance Computing (UHPC) program asked researchers to develop computing systems capable of achieving energy efficiencies of 50 GOPS/Watt, assuming 2018-era fabrication technologies. This paper describes Runnemede, the research architecture developed by the Intel-led UHPC team. Runnemede is being developed through a co-design process that considers the hardware, the runtime/OS,...
For applications that deal with large amounts of high dimensional multi-aspect data, it becomes natural to represent such data as tensors or multi-way arrays. Multi-linear algebraic computations such as tensor decompositions are performed for summarization and analysis of such data. Their use in real-world applications can span across domains such as signal processing, data mining, computer vision,...
A significant source for enhancing application performance and for reducing power consumption in embedded processor applications is to improve the usage of the memory hierarchy. In this paper, a temporal and spatial locality optimization framework of nested loops is proposed, driven by parameterized cost functions. The considered loops can be imperfectly nested. New data layouts are propagated through...
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.