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.
Elastic distributed storage systems have been increasingly studied in recent years because power consumption has become a major problem in data centers. Much progress has been made in improving the agility of resizing small- and large-scale distributed storage systems. However, most of these studies focus on metadata based distributed storage systems. On the other hand, emerging consistent hashing...
We present and evaluate a new GPU algorithm based on the Louvain method for community detection. Our algorithm is the first for this problem that parallelizes the access to individual edges. In this way we can fine tune the load balance when processing networks with nodes of highly varying degrees. This is achieved by scaling the number of threads assigned to each node according to its degree. Extensive...
Today, there is a steep rise in the amount of data being collected from diverse applications. Consequently, data analytic workloads are gaining popularity to gain insight that can benefit the application, e.g., financial trading, social media analysis. To study the architectural behavior of the workloads, architectural simulation is one of the most common approaches. However, because of the long-running...
To explore the potential of training complex deep neural networks (DNNs) on other commercial chips rather than GPUs, we report our work on swDNN, which is a highly-efficient library for accelerating deep learning applications on the newly announced world-leading supercomputer, Sunway TaihuLight. Targeting SW26010 processor, we derive a performance model that guides us in the process of identifying...
Interest has recently grown in efficiently analyzing unstructured data such as social network graphs and protein structures. A fundamental graph algorithm for doing such task is the Breadth-First Search (BFS) algorithm, the foundation for many other important graph algorithms such as calculating the shortest path or finding the maximum flow in graphs. In this paper, we share our experience of designing...
Matrix multiplication (GEMM) is a core operation to numerous scientific applications. Traditional implementations of Strassen-like fast matrix multiplication (FMM) algorithms often do not perform well except for very large matrix sizes, due to the increased cost of memory movement, which is particularly noticeable for non-square matrices. Such implementations also require considerable workspace and...
Current monitor based systems have some disadvantages for multi-object operations. They require the programmers to (1) manually determine the order of locking operations, (2) manually determine the points of execution where threads should signal other threads, (3) use global locks or perform busy waiting for operations that depend upon a condition that spans multiple objects. Transactional memory...
Dynamic vectors are among the most commonly used data structures in programming. They provide constant time random access and resizable data storage. Additionally, they provide constant time insertion (pushback) and deletion (popback) at the end of the sequence. However, in a multithreaded system, concurrent pushback and popback operations attempt to update the same shared object, creating a synchronization...
Limited power budgets will be one of the biggest challenges for deploying future exascale supercomputers. One of the promising ways to deal with this challenge is hardware overprovisioning, that is, installingmore hardware resources than can be fully powered under a given power limit coupled with software mechanisms to steer the limited power to where it is needed most. Prior research has demonstrated...
We give efficient algorithms to solve fundamental data movement problems on mesh-connected computers augmented with limited global bandwidth. Adding a small amount of global bandwidth makes a practical design that combines aspects of mesh and fully connected models to achieve the benefits of each. We give algorithms for sorting, finding the median, finding a spanning tree, and determining various...
We present the design and implementation of a parallel and fully algebraic preconditioner based on an approximate sparse factorization using low-rank matrix compression. The sparse factorization uses a multifrontal algorithm with fill-in occurring in dense frontal matrices. These frontal matrices are approximated as hierarchically semi-separable matrices, which are constructed using a randomized sampling...
Accelerators, such as GPUs, have proven to be highly successful in reducing execution time and power consumption of compute-intensive applications. Even though they are already used pervasively, they are typically supervised by general-purpose CPUs, which results in frequent control flow switches and data transfers as CPUs are handling all communication tasks. However, we observe that accelerators...
Deadlock avoidance mechanisms for lossless lowdistance networks typically increase the order of virtual channel (VC) index with each hop. This restricts the number of buffer resources depending on the routing mechanism and limits performance due to an inefficient use. Dynamic buffer organizations increase implementation complexity and only provide small gains in this context because a significant...
Today, big data applications can generate largescale data sets at an unprecedented rate; and scientists have turned to parallel and distributed systems for data analysis. Although many big data processing systems provide advanced mechanisms to partition data and tackle the computational skew, it is difficult to efficiently implement skew-resistant mechanisms, because the runtime of different partitions...
We introduce XtraPuLP, a new distributed-memory graph partitioner designed to process trillion-edge graphs. XtraPuLP is based on the scalable label propagation community detection technique, which has been demonstrated as a viable means to produce high quality partitions with minimal computation time. On a collection of large sparse graphs, we show that XtraPuLP partitioning quality is comparable...
We present a new parallel algorithm for solving triangular systems with multiple right hand sides (TRSM). TRSM is used extensively in numerical linear algebra computations, both to solve triangular linear systems of equations as well as to compute factorizations with triangular matrices, such as Cholesky, LU, and QR. Our algorithm achieves better theoretical scalability than known alternatives, while...
Designing a cost-effective network for data centers that can deliver sufficient bandwidth and provide high availability has drawn tremendous attentions recently. In this paper, we propose a novel server-centric network structure called RCube, which is energy efficient and can deploy a redundancy scheme to improve the availability of data centers. Moreover, RCube shares many good properties with BCube,...
Limited power budget is becoming one of the most crucial challenges in developing supercomputer systems. Hardware overprovisioning which installs a larger number of nodes beyond the limitations of the power constraint is an attractive way to design next generation supercomputers. In air cooled HPC centers, about half of the total power is consumed by cooling facilities. Reducing cooling power and...
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.