@article{MarrPapeDeMeuter2014,
  author    = {Marr, Stefan and Pape, Tobias and De Meuter, Wolfgang},
  title     = {Are we there yet? Simple language implementation techniques for the 21st century},
  series = {IEEE software},
  volume    = {31},
  journal   = {IEEE software},
  number    = {5},
  publisher = {Inst. of Electr. and Electronics Engineers},
  address   = {Los Alamitos},
  issn      = {0740-7459},
  pages     = {60 -- 67},
  year      = {2014},
  language  = {en}
}
@article{BaumanBolzHirschfeldetal.2015,
  author    = {Bauman, Spenser and Bolz, Carl Friedrich and Hirschfeld, Robert and Kirilichev, Vasily and Pape, Tobias and Siek, Jeremy G. and Tobin-Hochstadt, Sam},
  title     = {Pycket: A Tracing JIT for a Functional Language},
  series = {ACM SIGPLAN notices},
  volume    = {50},
  journal   = {ACM SIGPLAN notices},
  number    = {9},
  publisher = {Association for Computing Machinery},
  address   = {New York},
  issn      = {0362-1340},
  doi       = {10.1145/2784731.2784740},
  pages     = {22 -- 34},
  year      = {2015},
  abstract  = {We present Pycket, a high-performance tracing JIT compiler for Racket. Pycket supports a wide variety of the sophisticated features in Racket such as contracts, continuations, classes, structures, dynamic binding, and more. On average, over a standard suite of benchmarks, Pycket outperforms existing compilers, both Racket's JIT and other highly-optimizing Scheme compilers. Further, Pycket provides much better performance for Racket proxies than existing systems, dramatically reducing the overhead of contracts and gradual typing. We validate this claim with performance evaluation on multiple existing benchmark suites. The Pycket implementation is of independent interest as an application of the RPython meta-tracing framework (originally created for PyPy), which automatically generates tracing JIT compilers from interpreters. Prior work on meta-tracing focuses on bytecode interpreters, whereas Pycket is a high-level interpreter based on the CEK abstract machine and operates directly on abstract syntax trees. Pycket supports proper tail calls and first-class continuations. In the setting of a functional language, where recursion and higher-order functions are more prevalent than explicit loops, the most significant performance challenge for a tracing JIT is identifying which control flows constitute a loop-we discuss two strategies for identifying loops and measure their impact.},
  language  = {en}
}
@article{FreudenbergIngallsFelgentreffetal.2015,
  author    = {Freudenberg, Bert and Ingalls, Dan and Felgentreff, Tim and Pape, Tobias and Hirschfeld, Robert},
  title     = {SqueakJS A Modern and Practical Smalltalk that Runs in Any Browser},
  series = {ACM SIGPLAN notices},
  volume    = {50},
  journal   = {ACM SIGPLAN notices},
  number    = {2},
  publisher = {Association for Computing Machinery},
  address   = {New York},
  issn      = {0362-1340},
  doi       = {10.1145/10.1145/2661088.2661100},
  pages     = {57 -- 66},
  year      = {2015},
  abstract  = {We report our experience in implementing SqueakJS, a bitcompatible implementation of Squeak/Smalltalk written in pure JavaScript. SqueakJS runs entirely in theWeb browser with a virtual file system that can be directed to a server or client-side storage. Our implementation is notable for simplicity and performance gained through adaptation to the host object memory and deployment leverage gained through the Lively Web development environment. We present several novel techniques as well as performance measurements for the resulting virtual machine. Much of this experience is potentially relevant to preserving other dynamic language systems and making them available in a browser-based environment.},
  language  = {en}
}
@article{PapeFelgentreffHirschfeldetal.2016,
  author    = {Pape, Tobias and Felgentreff, Tim and Hirschfeld, Robert and Gulenko, Anton and Bolz, Carl Friedrich},
  title     = {Language-independent Storage Strategies for Tracing-JIT-based Virtual Machines},
  series = {ACM SIGPLAN notices},
  volume    = {51},
  journal   = {ACM SIGPLAN notices},
  publisher = {Association for Computing Machinery},
  address   = {New York},
  issn      = {0362-1340},
  doi       = {10.1145/2816707.2816716},
  pages     = {104 -- 113},
  year      = {2016},
  abstract  = {Storage strategies have been proposed as a run-time optimization for the PyPy Python implementation and have shown promising results for optimizing execution speed and memory requirements. However, it remained unclear whether the approach works equally well in other dynamic languages. Furthermore, while PyPy is based on RPython, a language to write VMs with reusable components such as a tracing just-in-time compiler and garbage collection, the strategies design itself was not generalized to be reusable across languages implemented using that same toolchain. In this paper, we present a general design and implementation for storage strategies and show how they can be reused across different RPython-based languages. We evaluate the performance of our implementation for RSqueak, an RPython-based VM for Squeak/Smalltalk and show that storage strategies may indeed off er performance benefits for certain workloads in other dynamic programming languages. We furthermore evaluate the generality of our implementation by applying it to Topaz, a Ruby VM, and Pycket, a Racket implementation.},
  language  = {en}
}
@article{PapeBolzHirschfeld2017,
  author    = {Pape, Tobias and Bolz, Carl Friedrich and Hirschfeld, Robert},
  title     = {Adaptive just-in-time value class optimization for lowering memory consumption and improving execution time performance},
  series = {Science of computer programming},
  volume    = {140},
  journal   = {Science of computer programming},
  publisher = {Elsevier},
  address   = {Amsterdam},
  issn      = {0167-6423},
  doi       = {10.1016/j.scico.2016.08.003},
  pages     = {17 -- 29},
  year      = {2017},
  abstract  = {The performance of value classes is highly dependent on how they are represented in the virtual machine. Value class instances are immutable, have no identity, and can only refer to other value objects or primitive values and since they should be very lightweight and fast, it is important to optimize them carefully. In this paper we present a technique to detect and compress common patterns of value class usage to improve memory usage and performance. The technique identifies patterns of frequent value object references and introduces abbreviated forms for them. This allows to store multiple inter-referenced value objects in an inlined memory representation, reducing the overhead stemming from meta data and object references. Applied to a small prototype and an implementation of the Racket language, we found improvements in memory usage and execution time for several micro-benchmarks. (C) 2016 Elsevier B.V. All rights reserved.},
  language  = {en}
}