PLDI

Machine-learning frameworks in Python, such as scikit-learn, Keras, Spark, or Pyro, use embedded domain specific languages (EDSLs) to assemble a computational graph. Unfortunately, these EDSLs make heavy use of strings as names for computational graph ...

The validation and deployment of novel research ideas in the field of Deep Learning is often limited by the availability of efficient compute kernels for certain basic primitives. In particular, operations that cannot leverage existing vendor libraries (...

HackPPL is a probabilistic programming language (PPL) built within the Hack programming language. Its universal inference engine allows developers to perform inference across a diverse set of models expressible in arbitrary Hack code. Through language-...

Searching repositories of existing source code for code snippets is a key task in software engineering. Over the years, many approaches to this problem have been proposed. One recent tool called NCS, takes in a natural language query and outputs ...

Good benchmarks are hard to find because they require a substantial effort to keep them representative for the constantly changing challenges of a particular field. Synthetic benchmarks are a common approach to deal with this, and methods from machine ...