Christian Grothoff

It is now well established that the device scaling predicted by Moore's Law is no longer a viable option for increasing the clock frequency of future uniprocessor systems at the rate that had been sustained during the last two decades. As a result, future systems are rapidly moving from uniprocessor to multiprocessor configurations, so as to use parallelism instead of frequency scaling as the foundation for increased compute capacity. The dominant emerging multiprocessor structure for the future is a Non-Uniform Cluster Computing (NUCC) system with nodes that are built out of multi-core SMP chips with non-uniform memory hierarchies, and interconnected in horizontally scalable cluster configurations such as blade servers. Unlike previous generations of hardware evolution, this shift will have a major impact on existing software. Current OO language facilities for concurrent and distributed programming are inadequate for addressing the needs of NUCC systems because they do not support the notions of non-uniform data access within a node, or of tight coupling of distributed nodes.We have designed a modern object-oriented programming language, X10, for high performance, high productivity programming of NUCC systems. A member of the partitioned global address space family of languages, X10 highlights the explicit reification of locality in the form of places}; lightweight activities embodied in async, future, foreach, and ateach constructs; a construct for termination detection (finish); the use of lock-free synchronization (atomic blocks); and the manipulation of cluster-wide global data structures. We present an overview of the X10 programming model and language, experience with our reference implementation, and results from some initial productivity comparisons between the X10 and Java™ languages.

It is now well established that the device scaling predicted by Moore's Law is no longer a viable option for increasing the clock frequency of future uniprocessor systems at the rate that had been sustained during the last two decades. As a result, future systems are rapidly moving from uniprocessor to multiprocessor configurations, so as to use parallelism instead of frequency scaling as the foundation for increased compute capacity. The dominant emerging multiprocessor structure for the future is a Non-Uniform Cluster Computing (NUCC) system with nodes that are built out of multi-core SMP chips with non-uniform memory hierarchies, and interconnected in horizontally scalable cluster configurations such as blade servers. Unlike previous generations of hardware evolution, this shift will have a major impact on existing software. Current OO language facilities for concurrent and distributed programming are inadequate for addressing the needs of NUCC systems because they do not support the notions of non-uniform data access within a node, or of tight coupling of distributed nodes.We have designed a modern object-oriented programming language, X10, for high performance, high productivity programming of NUCC systems. A member of the partitioned global address space family of languages, X10 highlights the explicit reification of locality in the form of places }; lightweight activities embodied in async , future , foreach , and ateach constructs; a construct for termination detection ( finish ); the use of lock-free synchronization ( atomic blocks ); and the manipulation of cluster-wide global data structures. We present an overview of the X10 programming model and language, experience with our reference implementation, and results from some initial productivity comparisons between the X10 and Java™ languages.

In 2005, Murdoch and Danezis demonstrated the first practical congestion attack against a deployed anonymity network. They could identify which relays were on a target Tor user’s path by building paths one at a time through every Tor relay and introducing congestion. However, the original attack was performed on only 13 Tor relays on the nascent and lightly loaded Tor network. We show that the attack from their paper is no longer practical on today’s 1500-relay heavily loaded Tor network. The attack doesn’t scale because a) the attacker needs a tremendous amount of bandwidth to measure enough relays during the attack window, and b) there are too many false positives now that many other users are adding congestion at the same time as the attacks. We then strengthen the original congestion attack by combining it with a novel bandwidth amplification attack based on a flaw in the Tor design that lets us build long circuits that loop back on themselves. We show that this new combination attack is practical and effective by demonstrating a working attack on today’s deployed Tor network. By coming up with a model to better understand Tor’s routing behavior under congestion, we further provide a statistical analysis characterizing how effective our attack is in each case. 1

Object-oriented languages provide little support for encapsulating objects. Reference semantics allows objects to escape their defining scope. The pervasive aliasing that ensues remains a major source of software defects. This paper introduces Kacheck/J a tool for inferring object encapulation properties in large Java programs. Our goal is to develop practical tools to assist software engineers, thus we focus on simple and scalable techniques. Kacheck/J is able to infer confinement for Java classes. A class and its sublasses are confined if all of their instances are encapsulated in their defining package. This simple property can be used to identify accidental leaks of sensitive objects. The analysis is scalable and efficient; Kacheck/J is able t infer confinement on a corpus of 46,000 classes (115 MB) in 6 minutes