This paper presents Poli-C, a language extension, runtime library, and system daemon enabling fine-grained, language-level, hierarchical resource management policies. Poli-C is suitable for use in applications that compose parallel libraries, frameworks, and programs. In particular, we have added a powerful new statement to C for expressing resource limits and guarantees in such a way that programmers can set resource management policies even when the source code of parallel libraries and frameworks is not available. Poli-C enables application programmers to manage any resource exposed by the underlying OS, for example cores or IO bandwidth. Additionally, we have developed a domain-specific language for defining high-level resource management policies, and a facility for extending the kinds of resources that can be managed with our language extension. Finally, through a number of useful variations, our design offers a high degree of composability. We evaluate Poli-C by way of three case-studies: a scientific application, an image processing webserver, and a pair of parallel database join implementations. We found that using Poli-C yields efficiency gains that require the addition of only a few lines of code to applications.

In this paper we introduce a new method for pessimistically implementing composable, nestable atomic statements. Our mechanism, called shelters, is inspired by the synchronization strategy used in the Jade programming language. Unlike previous lock-based pessimistic approaches, our mechanism does not require a whole-program analysis that computes a global lock order. Further, this mechanism frees us to implement several optimizations, impossible with automatically inserted locks, that are necessary for scaling on recent multi-core systems. Additionally we show how our basic mechanism can be extended to support both open- and closed-nesting of atomic statements, something that, to our knowledge, has not yet been implemented fully-pessimistically in this context. Unlike optimistic, transactional-memory-based approaches, programmers using our mechanism do not have to write compensating actions for open-nesting, or worry about the possibly awkward semantics and performance impact of aborted transactions.

SharC is a recently developed system for checking data-sharing in multithreaded programs. Programmers specify sharing rules (read-only, protected by a lock, etc.) for individual objects, and the SharC compiler enforces these rules using static and dynamic checks. Violations of these rules indicate unintended data sharing, which is the underlying cause of harmful data-races. Additionally, SharC allows programmers to change the sharing rules for a specific object using a sharing cast, to capture the fact that sharing rules for an object often change during the object's lifetime. SharC was successfully applied to a number of multi-threaded C programs.

Unintended or unmediated data sharing is a frequent cause of insidious bugs in multithreaded programs. We present a tool called SharC (short for Sharing Checker) that allows a user to write lightweight annotations to declare how they believe objects are being shared between threads in their program. SharC uses a combination of static and dynamic analyses to check that the program conforms to this specification.

Previous approaches for computing duplicate-sensitive aggregates in wireless sensor networks have used a tree topology, in order to conserve energy and to avoid double-counting sensor readings. However, a tree topology is not robust against node and communication failures, which are common in sensor networks. In this article, we present synopsis diffusion , a general framework for achieving significantly more accurate and reliable answers by combining energy-efficient multipath routing schemes with techniques that avoid double-counting. Synopsis diffusion avoids double-counting through the use of order- and duplicate-insensitive (ODI) synopses that compactly summarize intermediate results during in-network aggregation. We provide a surprisingly simple test that makes it easy to check the correctness of an ODI synopsis. We show that the properties of ODI synopses and synopsis diffusion create implicit acknowledgments of packet delivery. Such acknowledgments enable energy-efficient adaptation of message routes to dynamic message loss conditions, even in the presence of asymmetric links. Finally, we illustrate using extensive simulations the significant robustness, accuracy, and energy-efficiency improvements of synopsis diffusion over previous approaches.

Previous approaches for computing duplicate-sensitive aggregates in sensor networks (e.g., in TAG) have used a tree topology, in order to conserve energy and to avoid double-counting sensor readings. However, a tree topology is not robust against node and communication failures, which are common in sensor networks. In this paper, we present synopsis diffusion, a general framework for achieving signi.cantly more accurate and reliable answers by combining energy-efficient multi-path routing schemes with techniques that avoid double-counting. Synopsis diffusion avoids double-counting through the use of order- and duplicate-insensitive (ODI) synopses that compactly summarize intermediate results during in-network aggregation. We provide a surprisingly simple test that makes it easy to check the correctness of an ODI synopsis. We show that the properties of ODI synopses and synopsis di.usion create implicit acknowledgments of packet delivery. We show that this property can, in turn, enable the system to adapt message routing to dynamic message loss conditions, even in the presence of asymmetric links. Finally, we illustrate, using extensive simulations, the significant robustness, accuracy, and energy-efficiency improvements of synopsis diffusion over previous approaches.