Biblio

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2019-01-10
Christopher Hannon, Illinois Institute of Technology, Nandakishore Santhi, Los Alamos National Laboratory, Stephan Eidenbenz, Los Alamos National Laboratory, Jason Liu, Florida International University, Dong Jin, Illinois Institute of Technology.  2018.  Just-In-Time Parallel Simulation. 2018 Winter Simulation Conference (WSC).

Due to the evolution of programming languages, interpreted languages have gained widespread use in scientific and research computing. Interpreted languages excel at being portable, easy to use, and fast in prototyping than their ahead-of-time (AOT) counterparts, including C, C++, and Fortran. While traditionally considered as slow to execute, advancements in Just-in-Time (JIT) compilation techniques have significantly improved the execution speed of interpreted languages and in some cases outperformed AOT languages. In this paper, we explore some challenges and design strategies in developing a high performance parallel discrete event simulation engine, called Simian, written with interpreted languages with JIT capabilities, including Python, Lua, and Javascript. Our results show that Simian with JIT performs similarly to AOT simulators, such as MiniSSF and ROSS. We expect that with features like good performance, userfriendliness, and portability, the just-in-time parallel simulation will become a common choice for modeling and simulation in the near future.
 

2017-05-18
Chachmon, Nadav, Richins, Daniel, Cohn, Robert, Christensson, Magnus, Cui, Wenzhi, Reddi, Vijay Janapa.  2016.  Simulation and Analysis Engine for Scale-Out Workloads. Proceedings of the 2016 International Conference on Supercomputing. :22:1–22:13.

We introduce a system-level Simulation and Analysis Engine (SAE) framework based on dynamic binary instrumentation for fine-grained and customizable instruction-level introspection of everything that executes on the processor. SAE can instrument the BIOS, kernel, drivers, and user processes. It can also instrument multiple systems simultaneously using a single instrumentation interface, which is essential for studying scale-out applications. SAE is an x86 instruction set simulator designed specifically to enable rapid prototyping, evaluation, and validation of architectural extensions and program analysis tools using its flexible APIs. It is fast enough to execute full platform workloads–-a modern operating system can boot in a few minutes–-thus enabling research, evaluation, and validation of complex functionalities related to multicore configurations, virtualization, security, and more. To reach high speeds, SAE couples tightly with a virtual platform and employs both a just-in-time (JIT) compiler that helps simulate simple instructions efficiently and a fast interpreter for simulating new or complex instructions. We describe SAE's architecture and instrumentation engine design and show the framework's usefulness for single- and multi-system architectural and program analysis studies.