The SPLASH-2 suite of parallel applications has recently been released to facilitate the study of centralized and distributed shared-address-space multiprocessors. In this context, this paper has two goals. One is to quantitatively characterize the SPLASH-2 programs in terms of fundamental properties and architectural interactions that are important to understand them well. The properties we study include the computational load balance, communication to computation ratio and traffic needs, important working set sizes, and issues related to spatial locality, as well as how these properties scale with problem size and the number of processors. The other, related goal is methodological: to assist people who will use the programs in architectural evaluations to prune the space of application and machine parameters in an informed and meaningful way. For example, by characterizing the working sets of the applications, we describe which operating points in terms of cache size and problem size are representative of realistic situations, which are not, and which re redundant. Using SPLASH-2 as an example, we hope to convey the importance of understanding the interplay of problem size, number of processors, and working sets in designing experiments and interpreting their results.

/pdf/the-splash-2-programs-characterization-and-methodological-14b6i8va45.pdf

The SPLASH-2 programs: characterization and methodological considerations

We present the internals of QEMU, a fast machine emulator using an original portable dynamic translator. It emulates several CPUs (x86, PowerPC, ARM and Sparc) on several hosts (x86, PowerPC, ARM, Sparc, Alpha and MIPS). QEMU supports full system emulation in which a complete and unmodified operating system is run in a virtual machine and Linux user mode emulation where a Linux process compiled for one target CPU can be run on another CPU.

/pdf/qemu-a-fast-and-portable-dynamic-translator-xpb07ophlg.pdf

QEMU, a fast and portable dynamic translator

The determination of upper bounds on execution times, commonly called worst-case execution times (WCETs), is a necessary step in the development and validation process for hard real-time systems. This problem is hard if the underlying processor architecture has components, such as caches, pipelines, branch prediction, and other speculative components. This article describes different approaches to this problem and surveys several commercially available tools1 and research prototypes.

/pdf/the-worst-case-execution-time-problem-overview-of-methods-2kdq3gxkoy.pdf

The worst-case execution-time problem—overview of methods and survey of tools

http://www.inf.ufes.br/~luciac/comcie/JFNK-Knoll.pdf

Jacobian-free Newton-Krylov methods: a survey of approaches and applications

The most exciting development in parallel computer architecture is the convergence of traditionally disparate approaches on a common machine structure. This book explains the forces behind this convergence of shared-memory, message-passing, data parallel, and data-driven computing architectures. It then examines the design issues that are critical to all parallel architecture across the full range of modern design, covering data access, communication performance, coordination of cooperative work, and correct implementation of useful semantics. It not only describes the hardware and software techniques for addressing each of these issues but also explores how these techniques interact in the same system. Examining architecture from an application-driven perspective, it provides comprehensive discussions of parallel programming for high performance and of workload-driven evaluation, based on understanding hardware-software interactions.


* synthesizes a decade of research and development for practicing engineers, graduate students, and researchers in parallel computer architecture, system software, and applications development

* presents in-depth application case studies from computer graphics, computational science and engineering, and data mining to demonstrate sound quantitative evaluation of design trade-offs 

* describes the process of programming for performance, including both the architecture-independent and architecture-dependent aspects, with examples and case-studies

* illustrates bus-based and network-based parallel systems with case studies of more than a dozen important commercial designs

Table of Contents

1 Introduction 
2 Parallel Programs 
3 Programming for Performance 
4 Workload-Driven Evaluation 
5 Shared Memory Multiprocessors 
6 Snoop-based Multiprocessor Design 
7 Scalable Multiprocessors
8 Directory-based Cache Coherence
9 Hardware-Software Tradeoffs 
10 Interconnection Network Design 
11 Latency Tolerance 
12 Future Directions 
APPENDIX A Parallel Benchmark Suites

Parallel Computer Architecture: A Hardware/Software Approach

Many mobile devices have reached the point where the users' (active) working set is smaller than the amount of storage available and that trend is likely to continue. Currently these resources are made available for recording new data, but we think that we could make better use of this capacity. Hoarding previously not accessed data could give better data coverage in cases of disconnected operation, when wireless networks are not available or access to them is expensive.We gathered a trace from a university file system used by more than 5000 people over a period of 16 months. This trace is used to drive a simulation model of distributed file systems. This paper studies a novel hoarding scheme that uses the access profile of other users to predict what files a user would need in the future. This hoarding scheme is shown to avoid between 30% and 75% of remote file accesses to files that are accessed for the first time. Furthermore, hoarded but not used data can be expired, because we note experimentally that the population shifts focus each month.

https://www2.computer.org/portal/web/csdl/doi/10.1109/ICIS.2009.164

Per Stenström

Papers

Using Hoarding to Increase Availability in Shared File Systems