TL;DR
Torchy is presented, a tracing JIT compiler for PyTorch, one of the mainstream eager-mode frameworks, that achieves similar performance as data-flow frameworks, while providing the same semantics of straight-away execution.
FlowLog is demonstrated, a Datalog compiler that turns Souffl\'e-style programs into Differential Dataflow executables for efficient and extensible static analysis and consistently outperforms state-of-the-art engines in runtime while remaining memory-efficient and scaling better.
This article presents a novel technique for reducing the size of AOT compiled programs by using fully-context-sensitive profiles to concentrate the optimizations on the hot code.
We propose PKDB, the first interactive debugger for GPU and multithreaded low-level kernels written in Python. Python is widely used in high performance computing (HPC), with frameworks such as PyKokkos translating Python-embedded domain-specific languages to native code that runs across OpenMP-threaded CPUs and variou...
This work creates an “over language” in which to express all the information the authors need to be able to output correct and idiomatic syntax for each of their targets, and details the design of the extensible system.
This paper explores copy-and-patch as a foundation for dynamic program analysis, and implements four analyses on top of an existing copy-and-patch JIT for R: code instrumentation, code coverage, performance profiling, and native debugging.
A strongly typed domain-specific language with Haskell-like syntax, that enables a write-once, run everywhere paradigm for LLM architectures, Axon fosters open cooperation and empowers researchers to implement highly specialized architectures without giving up optimization infrastructure or accepting deployment lock-in...
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