Through-Silicon Interposer (TSI) has recently been proposed to provide high memory bandwidth and improve energy efficiency of the main memory system. However, the impact of TSI on main memory system architecture has not been well explored. While TSI ...

The cache hierarchy often consumes a large portion of a processor's energy. To save energy in HPC environments, this paper proposes software-controlled reconfiguration of the cache hierarchy with an adaptive runtime system. Our approach addresses the ...

Anton 2 is a second-generation special-purpose supercomputer for molecular dynamics simulations that achieves significant gains in performance, programmability, and capacity compared to its predecessor, Anton 1. The architecture of Anton 2 is tailored ...

Servers and HPC systems often use a strong memory error correction code, or ECC, to meet their reliability and availability requirements. However, these ECCs often require significant capacity and/or power overheads. We observe that since memory ...

The ever increasing amount of data generated by scientific simulations coupled with system I/O constraints are fueling a need for in-situ analysis techniques. Of particular interest are approaches that produce reduced data representations while ...

Stream surfaces and streamlines are two popular methods for visualizing three-dimensional flow fields. While several parallel streamline computation algorithms exist, relatively little research has been done to parallelize stream surface generation. ...

Computing a Voronoi or Delaunay tessellation from a set of points is a core part of the analysis of many simulated and measured datasets: N-body simulations, molecular dynamics codes, and LIDAR point clouds are just a few examples. Such computational ...

Network performance aware optimizations have long been an effective approach to optimizing distributed applications on traditional network environments. However, the assumptions of network topology or direct use of several measurements of pair-wise ...

Resource sharing in virtualized environments have been demonstrated significant benefits to improve application performance and resource/energy efficiency. However, resource sharing, especially for multiple resource types, poses several severe and ...

Load imbalance is a major source of overhead in Hadoop where the uneven distribution of input data among tasks can significantly delays the job completion. Running Hadoop in a private cloud opens up opportunities for mitigating data skew with elastic ...

A new sparse high performance conjugate gradient benchmark (HPCG) has been recently released to address challenges in the design of sparse linear solvers for the next generation extreme-scale computing systems. Key computation, data access, and ...

Krylov subspace projection methods are widely used iterative methods for solving large-scale linear systems of equations. Researchers have demonstrated that communication-avoiding (CA) techniques can improve Krylov methods' performance on modern ...

Many sparse matrix computations can be speeded up if the matrix is first reordered. Reordering was originally developed for direct methods but it has recently become popular for improving the cache locality of parallel iterative solvers since reordering ...

Drawing on neuroscience, we have developed a parallel, event-driven kernel for neurosynaptic computation, that is efficient with respect to computation, memory, and communication. Building on the previously demonstrated highly-optimized software ...

Future extreme-scale systems are expected to experience different types of failures affecting applications with different failure scales, from transient uncorrectable memory errors in processes to massive system outages. In this paper, we propose a ...

Application resilience is a key challenge that must be addressed in order to realize the exascale vision. Process/node failures, an important class of failures, are typically handled today by terminating the job and restarting it from the last stored ...

Fault-tolerance poses a major challenge for future large-scale systems. Active research into coordinated, uncoordinated, and hybrid checkpointing systems has explored how the introduction of asynchrony can address anticipated scalability issues. However,...

Several emerging trends are pointing to increasing heterogeneity among nodes and/or cores in HPC systems. Existing programming models, especially for distributed memory execution, typically have been designed to facilitate high performance on ...

We present an approach to improving data locality across different phases of fork/join programs scheduled using work stealing. The approach consists of: (1) user-specified and automated approaches to constructing a steal tree, the schedule of steal ...

Applications on modern supercomputers are increasingly limited by the cost of data movement, but mainstream programming systems have few abstractions for describing the structure of a program's data. Consequently, the burden of managing data movement, ...