Rosetta Stones and Cuneiform Tablets

This chapter examines the role in the marker design of buried objects intended to be inscribed with messages. Modeled on works like the Rosetta Stone, the stele of Hammurabi, and cuneiform tablets, this part of the design turned the marker system into an artificial archaeological site. Debates are explored about how meanings are effectively communicated, with an emphasis on parallel languages as securing transmission of meaning countered by historical evidence of English literary texts that rapidly became difficult to read. The chapter explores how Rosetta Stone came to be treated as a metaphor for a key to decipherment that would have been familiar to the expert consultants. Archaeological context demonstrates that the models used never actually were aimed to communicate into long-term futures. An interlude after the chapter explores the experts’ understanding of how Land Art worked, and how the artists creating such works understood them.

A Semantic Framework to Debug Parallel Lazy Functional Languages

It is not easy to debug lazy functional programs. The reason is that laziness and higher-order complicates basic debugging strategies. Although there exist several debuggers for sequential lazy languages, dealing with parallel languages is much harder. In this case, it is important to implement debugging platforms for parallel extensions, but it is also important to provide theoretical foundations to simplify the task of understanding the debugging process. In this work, we deal with the debugging process in two parallel languages that extend the lazy language Haskell. In particular, we provide an operational semantics that allows us to reason about our parallel extension of the sequential debugger Hood. In addition, we show how we can use it to analyze the amount of speculative work done by the processes, so that it can be used to optimize their use of resources.

Translating Performance

This chapter reflects on the doubleness of translation as the condition of existence of Asian performances of Shakespeare. It begins with the experience of hearing echoes of the original English lines when listening to Shakespeare’s texts translated into a language one does not speak. To address the interculturality of reception of Asian Shakespeare performances, the Asian Shakespeare Intercultural Archive (A|S|I|A, http://a-s-i-a-web.org), a collaborative project by scholars, translators, and practitioners, developed an approach to archiving production videos, scripts, and data in four parallel languages: English, Chinese, Japanese and Korean. The chapter examines the A|S|I|A archival process in relation to the position of the English scripts in multidirectional translations, and to the detailed data created by the project team. It concludes by positing comparative research into the use of the ‘traditional’ by tracing the varying occurrences of the term in the data.

Oracle-guided scheduling for controlling granularity in implicitly parallel languages

A classic problem in parallel computing is determining whether to execute a thread in parallel or sequentially. If small threads are executed in parallel, the overheads due to thread creation can overwhelm the benefits of parallelism, resulting in suboptimal efficiency and performance. If large threads are executed sequentially, processors may spin idle, resulting again in sub-optimal efficiency and performance. This “granularity problem” is especially important in implicitly parallel languages, where the programmer expresses all potential for parallelism, leaving it to the system to exploit parallelism by creating threads as necessary. Although this problem has been identified as an important problem, it is not well understood—broadly applicable solutions remain elusive. In this paper, we propose techniques for automatically controlling granularity in implicitly parallel programming languages to achieve parallel efficiency and performance. To this end, we first extend a classic result, Brent's theorem (a.k.a. the work-time principle) to include thread-creation overheads. Using a cost semantics for a general-purpose language in the style of lambda calculus with parallel tuples, we then present a precise accounting of thread-creation overheads and bound their impact on efficiency and performance. To reduce such overheads, we propose an oracle-guided semantics by using estimates of the sizes of parallel threads. We show that, if the oracle provides accurate estimates in constant time, then the oracle-guided semantics reduces the thread-creation overheads for a reasonably large class of parallel computations. We describe how to approximate the oracle-guided semantics in practice by combining static and dynamic techniques. We require the programmer to provide the asymptotic complexity cost for each parallel thread and use runtime profiling to determine hardware-specific constant factors. We present an implementation of the proposed approach as an extension of the Manticore compiler for Parallel ML. Our empirical evaluation shows that our techniques can reduce thread-creation overheads, leading to good efficiency and performance.