3750

Posts

Apr, 19

HPP-Controller: An intra-node controller designed for connecting heterogeneous CPUs

Heterogeneity is considered as a solution for supercomputers to scale to petascale. Many systems which are composed of general CPUs and special processing units such as Cells, GPGPUs and FPGAs have been implemented. In these systems, CPU needs interact with special processing units to process data together, thus communications between these heterogeneous processing units become […]
Apr, 19

Single-Chip Heterogeneous Computing: Does the Future Include Custom Logic, FPGAs, and GPGPUs?

To extend the exponential performance scaling of future chip multiprocessors, improving energy efficiency has become a first-class priority. Single-chip heterogeneous computing has the potential to achieve greater energy efficiency by combining traditional processors with unconventional cores (U-cores) such as custom logic, FPGAs, or GPGPUs. Although U-cores are effective at increasing performance, their benefits can also […]
Apr, 19

Parallel Approaches for SWAMP Sequence Alignment

This document is a summary and overview of several approaches to implement the local sequence alignment algorithms known as SWAMP and SWAMP+ on commercially available hardware. Using a Smith-Waterman style of alignment, these parallel algorithms have several innovative extensions that take advantage of the ASC associative computing model while maintaining speed, accuracy, and producing a […]
Apr, 19

A Hybrid Analytical DRAM Performance Model

As process technology scales, the number of transistors that can fit in a unit area has increased exponentially. Processor throughput, memory storage, and memory throughput have all been increasing at an exponential pace. As such, DRAM has become an ever-tightening bottleneck for applications with irregular memory access patterns. Computer architects in industry sometimes use ad […]
Apr, 19

Extending the Scalability of Single Chip Stream Processors with On-chip Caches

As semiconductor scaling continues, more transistors can be put onto the same chip despite growing challenges in clock frequency scaling. Stream processor architectures can make effective use of these additional resources for appropriate applications. However, it is important that programmer effort be amortized across future generations of stream processor architectures. Current industry projections suggest a […]
Apr, 19

A Task-centric Memory Model for Scalable Accelerator Architectures

This paper presents a task-centric memory model for 1000-core compute accelerators. Visual computing applications are emerging as an important class of workloads that can exploit 1000-core processors. In these workloads, we observe data sharing and communication patterns that can be leveraged in the design of memory systems for future 1000-core processors. Based on these insights, […]
Apr, 19

Dynamic warp formation: Efficient MIMD control flow on SIMD graphics hardware

Recent advances in graphics processing units (GPUs) have resulted in massively parallel hardware that is easily programmable and widely available in today’s desktop and notebook computer systems. GPUs typically use single-instruction, multiple-data (SIMD) pipelines to achieve high performance with minimal overhead for control hardware. Scalar threads running the same computing kernel are grouped together into […]
Apr, 19

Dynamic detection of uniform and affine vectors in GPGPU computations

We present a hardware mechanism which dynamically detects uniform and affine vectors used in SPMD architecture such as Graphics Processing Units, to minimize pressure on the register file and reduce power consumption with minimal architectural modifications. A preliminary experimental analysis conducted with the Barra simulator shows that this optimization can benefit up to 34 % […]
Apr, 19

Parallel calculation of the median and order statistics on GPUs with application to robust regression

We present and compare various approaches to a classical selection problem on Graphics Processing Units (GPUs). The selection problem consists in selecting the $k$-th smallest element from an array of size $n$, called $k$-th order statistic. We focus on calculating the median of a sample, the $n/2$-th order statistic. We introduce a new method based […]
Apr, 19

A pseudospectral matrix method for time-dependent tensor fields on a spherical shell

We construct a pseudospectral method for the solution of time-dependent, non-linear partial differential equations on a three-dimensional spherical shell. The problem we address is the treatment of tensor fields on the sphere. As a test case we consider the evolution of a single black hole in numerical general relativity. A natural strategy would be the […]
Apr, 18

Building a Personal High Performance Computer with Heterogeneous Processors

Personal high performance computer (PHPC) requires lower cost and high performance. The Teraflops PHPC systems with special accelerator units like GPGPU have been presented, but they have difficulties in programming, compatibility and applicability. In this paper, we present HPP-PHPC, a hybrid architecture of heterogeneous processors connected by non-coherent off-chip system bus. The performance of HPP-PHPC […]
Apr, 18

Practical Pre-stack Kirchhoff Time Migration of Seismic Processing on General Purpose GPU

In this paper, we introduced three prototypes of GPGPU solutions on NVidia GeForce8800GT for a practical Pre-stack Kirchhoff Time Migration program. We presented how to re-design and re-implement the original CPU code to efficiency GPU code. The prototypes are more than at most 7.2 times faster than its CPU version on Intel’s P4 3.0G.
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Free GPU computing nodes at hgpu.org

Registered users can now run their OpenCL application at hgpu.org. We provide 1 minute of computer time per each run on two nodes with two AMD and one nVidia graphics processing units, correspondingly. There are no restrictions on the number of starts.

The platforms are

Node 1
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  • GPU device 1: AMD/ATI Radeon HD 6970 2GB, 880MHz
  • CPU: AMD Phenom II X6 @ 2.8GHz 1055T
  • RAM: 12GB
  • OS: OpenSUSE 13.1
  • SDK: nVidia CUDA Toolkit 6.5.14, AMD APP SDK 3.0
Node 2
  • GPU device 0: AMD/ATI Radeon HD 7970 3GB, 1000MHz
  • GPU device 1: AMD/ATI Radeon HD 5870 2GB, 850MHz
  • CPU: Intel Core i7-2600 @ 3.4GHz
  • RAM: 16GB
  • OS: OpenSUSE 12.3
  • SDK: AMD APP SDK 3.0

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