There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

We will review some of the major results in random graphs and some of the more challenging open problems. We will cover algorithmic and structural questions. We will touch on newer models, including those related to the WWW.

Random graphs

"Grid" computing has emerged as an important new field, distinguished from conventional distributed computing by its focus on large-scale resource sharing, innovative applications, and, in some cases, high performance orientation. In this article, the authors define this new field. First, they review the "Grid problem," which is defined as flexible, secure, coordinated resource sharing among dynamic collections of individuals, institutions, and resources--what is referred to as virtual organizations. In such settings, unique authentication, authorization, resource access, resource discovery, and other challenges are encountered. It is this class of problem that is addressed by Grid technologies. Next, the authors present an extensible and open Grid architecture, in which protocols, services, application programming interfaces, and software development kits are categorized according to their roles in enabling resource sharing. The authors describe requirements that they believe any such mechanisms must satisfy and discuss the importance of defining a compact set of intergrid protocols to enable interoperability among different Grid systems. Finally, the authors discuss how Grid technologies relate to other contemporary technologies, including enterprise integration, application service provider, storage service provider, and peer-to-peer computing. They maintain that Grid concepts and technologies complement and have much to contribute to these other approaches.

The Anatomy of the Grid: Enabling Scalable Virtual Organizations

Cloud Computing, the long-held dream of computing as a utility, has the potential to transform a large part of the IT industry, making software even more attractive as a service and shaping the way IT hardware is designed and purchased. Developers with innovative ideas for new Internet services no longer require the large capital outlays in hardware to deploy their service or the human expense to operate it. They need not be concerned about overprovisioning for a service whose popularity does not meet their predictions, thus wasting costly resources, or underprovisioning for one that becomes wildly popular, thus missing potential customers and revenue. Moreover, companies with large batch-oriented tasks can get results as quickly as their programs can scale, since using 1000 servers for one hour costs no more than using one server for 1000 hours. This elasticity of resources, without paying a premium for large scale, is unprecedented in the history of IT. Cloud Computing refers to both the applications delivered as services over the Internet and the hardware and systems software in the datacenters that provide those services. The services themselves have long been referred to as Software as a Service (SaaS). The datacenter hardware and software is what we will call a Cloud. When a Cloud is made available in a pay-as-you-go manner to the general public, we call it a Public Cloud; the service being sold is Utility Computing. We use the term Private Cloud to refer to internal datacenters of a business or other organization, not made available to the general public. Thus, Cloud Computing is the sum of SaaS and Utility Computing, but does not include Private Clouds. People can be users or providers of SaaS, or users or providers of Utility Computing. We focus on SaaS Providers (Cloud Users) and Cloud Providers, which have received less attention than SaaS Users. From a hardware point of view, three aspects are new in Cloud Computing.

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Above the Clouds: A Berkeley View of Cloud Computing

A 2001 IBM manifesto observed that a looming software complexity crisis -caused by applications and environments that number into the tens of millions of lines of code - threatened to halt progress in computing. The manifesto noted the almost impossible difficulty of managing current and planned computing systems, which require integrating several heterogeneous environments into corporate-wide computing systems that extend into the Internet. Autonomic computing, perhaps the most attractive approach to solving this problem, creates systems that can manage themselves when given high-level objectives from administrators. Systems manage themselves according to an administrator's goals. New components integrate as effortlessly as a new cell establishes itself in the human body. These ideas are not science fiction, but elements of the grand challenge to create self-managing computing systems.

The vision of autonomic computing

Today's computing systems pay a heavy "OS tax", as kernel execution accounts for a significant amount of resource footprint. This is not least because today's kernels abound with hardcoded heuristics that are designed with unstated assumptions, which rarely generalize well for diversifying applications and device technologies. We propose the concept of reconfigurable kernel datapaths that enables kernels to self-optimize dynamically. In this architecture, optimizations are computed from empirical data using machine learning (ML), and they are integrated into the kernel in a safe and systematic manner via an in-kernel virtual machine. This virtual machine implements the reconfigurable match table (RMT) abstraction, where tables are installed into the kernel at points where performance-critical events occur, matches look up the current execution context, and actions encode context-specific optimizations computed by ML, which may further vary from application to application. Our envisioned architecture will support both offline and online learning algorithms, as well as varied kernel subsystems. An RMT verifier will check program well-formedness and model efficiency before admitting an RMT program to the kernel. An admitted program can be interpreted in bytecode or just-in-time compiled to optimize the kernel datapaths.

Toward reconfigurable kernel datapaths with learned optimizations

SOSP 09 - Proceedings of the 22nd ACM SIGOPS Symposium on Operating Systems Principles

Thread Management for Shared-Memory Multiprocessors.

Threads, or \lightweight processes," have become a common and necessary component of new languages and operating systems. Threads allow the programmer or compiler to express, create, and control parallel activities, contributing to the structure and performance of programs. In this article, we discuss the many alternatives that present themselves when designing a support system for threads on a shared-memory multiprocessor. These alternatives innuence the ease, granularity, and performance of parallel programming. We conclude with a brief survey of three contemporary thread management systems (Windows NT, Presto, and Multilisp), using them to illustrate the issues raised in this article.

Thread Management for Shared-Memory Multiprocessors

The Workshop on Organizing Workshops, Conferences, and Symposia for Computer Systems (WOWCS) was organized to "bring together conference organizers (past, present, and future) and other interested people to discuss the issues they confront." In addition to the position papers submitted to the workshop, the WOWCS program committee has collected a bibliography of previous publications in this area. We also list some topics about which we wish we had received submissions, but did not; these could be good topics for future articles.

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Thomas Anderson

Papers

Toward reconfigurable kernel datapaths with learned optimizations

SOSP 09 - Proceedings of the 22nd ACM SIGOPS Symposium on Operating Systems Principles

Thread Management for Shared-Memory Multiprocessors.

Thread Management for Shared-Memory Multiprocessors

Before and after WOWCS: a literature survey, a list of papers we wish had been submitted