Walter B. Ligon

A re-evaluation of the practicality of floating-point operations on FPGAs

The use of reconfigurable hardware to perform high precision operations such as IEEE floating point operations has been limited in the past by FPGA resources. We discuss the implementation of IEEE single precision floating-point multiplication and addition. Then, we assess the practical implications of using these operations in the Xilinx 4000 series FPGAs considering densities available now and scheduled for the near future. For each operation, we present space requirements and performance information. This is followed by a discussion of an algorithm, matrix multiplication, based on these operations, which achieves performance comparable to conventional microprocessors. Algorithm implementation options and their performance implications are discussed and corresponding measured results are given.

Implementation and performance of a parallel file system for high performance distributed applications

Dedicated cluster parallel computers (DCPCs) are emerging as low-cost high performance environments for many important applications in science and engineering. A significant class of applications that perform well on a DCPC are coarse-grain applications that involve large amounts of file I/O. Current research in parallel file systems for distributed systems is providing a mechanism for adapting these applications to the DCPC environment. We present the Parallel Virtual File System (PVFS), a system that provides disk striping across multiple nodes in a distributed parallel computer and file partitioning among tasks in a parallel program. PVFS is unique among similar systems in that it uses a stream-based approach that represents each file access with a single set of request parameters and decouples the number of network messages from details of the file striping and partitioning. PVFS also provides support for efficient collective file accesses and allows overlapping file partitions. We present results of early performance experiments that show PVFS achieves excellent speedups in accessing moderately sized file segments.

Characterization of Bandwidth-Aware Meta-Schedulers for Co-Allocating Jobs Across Multiple Clusters

In this paper, we present a bandwidth-centric job communication model that captures the interaction and impact of simultaneously co-allocating jobs across multiple clusters. We compare our dynamic model with previous research that utilizes a fixed execution time penalty for co-allocated jobs. We explore the interaction of simultaneously co-allocated jobs and the contention they often create in the network infrastructure of a dedicated computational multi-cluster.We also present several bandwidth-aware co-allocating meta-schedulers. These schedulers take inter-cluster network utilization into account as a means by which to mitigate degraded job run-time performance. We make use of a bandwidth-centric parallel job communication model that captures the time-varying utilization of shared inter-cluster network resources. By doing so, we are able to evaluate the performance of multi-cluster scheduling algorithms that focus not only on node resource allocation, but also on shared inter-cluster network bandwidth.

BMI: a network abstraction layer for parallel I/O

As high-performance computing increases in popularity and performance, the demand for similarly capable input and output systems rises. Parallel I/O takes advantage of many data server machines to provide linearly scaling performance to parallel applications that access storage over the system area network. The demands placed on the network by a parallel storage system are considerably different than those imposed by message-passing algorithms or data-center operations; and, there are many popular and varied networks in use in modern parallel machines. These considerations lead us to develop a network abstraction layer for parallel I/O which is efficient and thread-safe, provides operations specifically required for I/O processing, and supports multiple networks. The buffered message interface (BMI) has low processor overhead, minimal impact on latency, and can improve throughput for parallel file system workloads by as much as 40% compared to other more generic network abstractions.

Using server-to-server communication in parallel file systems to simplify consistency and improve performance

The trend in parallel computing toward clusters running thousands of cooperating processes per application has led to an I/O bottleneck that has only gotten more severe as the CPU density of clusters has increased. Current parallel file systems provide large amounts of aggregate I/O bandwidth; however, they do not achieve the high degrees of metadata scalability required to manage files distributed across hundreds or thousands of storage nodes. In this paper we examine the use of collective communication between the storage servers to improve the scalability of file metadata operations. In particular, we apply server-to-server communication to simplify consistency checking and improve the performance of file creation, file removal, and file stat. Our results indicate that collective communication is an effective scheme for simplifying consistency checks and significantly improving the performance for several real metadata intensive workloads.

Bandwidth-aware co-allocating meta-schedulers for mini-grid architectures

The interaction of simultaneously co-allocated jobs can often create contention in the network infrastructure of a dedicated computational grid. This contention can lead to degraded job run-time performance. We present several bandwidth-aware co-allocating meta-schedulers. These schedulers take into account inter-cluster network utilization as a means by which to mitigate this impact. We make use of a bandwidth-centric parallel job communication model that captures the time-varying utilization of shared inter-cluster network resources. By doing so, we are able to evaluate the performance of grid scheduling algorithms that focus not only on node resource allocation, but also on shared inter-cluster network bandwidth.

An evaluation of message passing implementations on Beowulf workstations

Beowulf workstations have become a popular choice for high-end computing in a number of application domains. One of the key building blocks of parallel applications on Beowulf workstations is a message passing library. While there are message passing library implementations available for use on Beowulf workstations, as of yet none have been specifically tailored to this new, unique architecture. Thus it is important to evaluate the existing packages in order to determine how these perform in this environment. This paper examines a set of four message passing libraries available for Beowulf workstations, focusing on their features, implementation, reliability, and performance. From this evaluation we identify the strengths and weaknesses of the packages and point out how implementations might be optimized to better suit the Beowulf environment.

Job communication characterization and its impact on meta-scheduling co-allocated jobs in a mini-grid

Summary form only given. We present a bandwidth-centric parallel job communication model that takes into account inter-cluster network utilization as a means by which to capture the interaction and impact of simultaneously co-allocated jobs in a mini-grid. Our model captures the time-varying utilization of shared inter-cluster network resources in the grid. We compare our dynamic model with previous research that utilizes a fixed execution time penalty for co-allocated jobs. We have found that the fixed penalty model is more generous in its prediction of job turnaround time than our dynamic communication model. Additionally, we see that the penalty co-allocated jobs may experience without causing a severe performance degradation decreases as the number of clusters increases.

A reconfigurable extension to the network interface of beowulf clusters

With a focus on commodity PC systems, Beowulf clusters traditionally lack the cutting edge network architectures, memory subsystems, and processor technologies found in their more expensive supercomputer counterparts. What Beowulf clusters lack in technology, they more than make up for with their significant cost advantage over traditional supercomputers. We propose an architectural extension that adds reconfigurable computing to the network interface of Beowulf clusters. This enhances both the network and processor capabilities of the cluster.Furthermore, for some applications, the proposed extension partially compensates for weaknesses in the PC memory subsystem.We discuss two applications, the 2D Fast Fourier Transform (FFT) and integer sorting, which benefit from the resulting architecture.

Analysis of a prototype intelligent network interface

With a focus on commodity PC systems, Beowulf clusters traditionally lack the cutting edge network architectures, memory subsystems, and processor technologies found in their more expensive supercomputer counterparts. Many users find that what Beowulf clusters lack in technology, they more than make up for with their significant cost advantage. In this paper, an architectural extension that adds reconfigurable computing to the network interface of Beowulf clusters is proposed. The proposed extension, called an intelligent network interface card (or INIC), enhances both the network and processor capabilities of the cluster, which has a significant impact on the performance of a crucial class of applications. Furthermore, for some applications, the proposed extension partially compensates for weaknesses in the PC memory subsystem. A prototype of the proposed architecture was constructed and analyzed. In addition, two applications, the 2D Fast Fourier Transform (2D‐FFT) and integer sorting, which benefit from the resulting architecture, are discussed and analyzed on the proposed architecture. Specifically, results indicate that the 2D‐FFT is performed 15–50% faster when using the prototype INIC rather than the comparable Gigabit Ethernet. Early simulation results also indicate that integer sorting will receive a 21–32% performance boost from the prototype. The significant improvements seen with a relatively limited prototype lead to the conclusion that cluster network interfaces enhanced with reconfigurable computing could significantly improve the Beowulf architecture. Copyright