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In computer science, a tail call is a subroutine call performed as the final action of a procedure. If the target of a tail is the same subroutine, the subroutine is said to be tail recursive, which is a special case of direct recursion. Tail recursion (or tail-end recursion) is particularly useful, and is often easy to optimize in implementations. Tail calls can be implemented without adding a new stack frame to the call stack. Most of the frame of the current procedure is no longer needed, and can be replaced by the frame of the tail call, modified as appropriate (similar to overlay for processes, but for function calls). The program can then jump to the called subroutine. Producing such code instead of a standard call sequence is called tail-call elimination or tail-call optimization. Tail-call elimination allows procedure calls in tail position to be implemented as efficiently as goto statements, thus allowing efficient structured programming. In the words of Guy L. Steele, "in

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Tail Call Elimination on the Java Virtual Machine

Martin Odersky, Michel Schinz

A problem that often has to be solved by compilers for functional languages targeting the Java Virtual Machine is the elimination of tail calls. This paper explains how we solved it in our Funnel compiler and presents some experimental results about the impact our technique has on both performance and size of the compiled programs.

2001

Caching All Plans with Just One Optimizer Call

Anastasia Ailamaki, Ioannis Alagiannis, Debabrata Dash, Cristina Ileana Maier

Modern database management systems (DBMS) answer a multitude of complex queries on increasingly larger datasets. Given the complexities of the queries and the numerous design features, manual design is no longer an option. Instead, automatically designing the database is vital to maximize its performance and to reduce the total cost of ownership. For this purpose, commercial DBMS feature automated physical designers suggesting an efficient DB design by using the optimizer as a cost model. Unfortunately, consulting the optimizer is timeconsuming, an effect which is typically counter-acted by drastically pruning the search space, thereby potentially missing the optimal solution. Recently techniques cache the optimizer’s output and evaluate some plans with the cached results, reducing the number of calls to the optimizer. Still, however, the cost of invoking the optimizer to fill the cache is nontrivial, undermining scalability when running workloads with thousands of queries. In this paper, we use the intermediate optimization results in a dynamic programming based optimizer to reduce the cache initialization overhead. We demonstrate the accuracy and efficiency of our techniques by implementing them on the PostgreSQL open source query optimizer. For a star-schema workload, our techniques build the cost model 5 to 10 times faster than the conventional approach, while preserving accuracy.

2010

Compact solid-state CMOS single-photon detector array for in vivo NIR fluorescence lifetime oncology measurements

Claudio Bruschini, Edoardo Charbon, Krisztian Homicsko, Harald Arjan Robert Homulle, François Eric Powolny, Riccardo Sinisi

In near infrared fluorescence-guided surgical oncology, it is challenging to distinguish healthy from cancerous tissue. One promising research avenue consists in the analysis of the exogenous fluorophores' lifetime, which are however in the (sub-)nanosecond range. We have integrated a single-photon pixel array, based on standard CMOS SPADs (single-photon avalanche diodes), in a compact, time-gated measurement system, named FluoCam. In vivo measurements were carried out with indocyanine green (ICG)-modified derivatives targeting the alpha(v)beta(3) integrin, initially on a genetically engineered mouse model of melanoma injected with ICG conjugated with tetrameric cyclic pentapeptide (ICG-E[c(RGDfK)(4)]), then on mice carrying tumour xenografts of U87-MG (a human primary glioblastoma cell line) injected with monomeric ICG c (RGDfK). Measurements on tumor, muscle and tail locations allowed us to demonstrate the feasibility of in vivo lifetime measurements with the FluoCam, to determine the characteristic lifetimes (around 500 ps) and subtle lifetime differences between bound and unbound ICG-modified fluorophores (10% level), as well as to estimate the available photon fluxes under realistic conditions. (C) 2016 Optical Society of America

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