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Revisiting Computation for Research: Practices and Trends

https://doi.org/10.1109/SC41406.2024.00076

Giordani, Jeremiah; Xu, Ziyang; Colby, Ella; Ning, August; Godala, Bhargav Reddy; Chaturvedi, Ishita; Zhu, Shaowei; Chon, Yebin; Chan, Greg; Tan, Zujun; et al (November 2024, IEEE)

Free, publicly-accessible full text available November 17, 2025
GhOST: a GPU Out-of-Order Scheduling Technique for Stall Reduction

https://doi.org/10.1109/ISCA59077.2024.00011

Chaturvedi, Ishita; Godala, Bhargav Reddy; Wu, Yucan; Xu, Ziyang; Iliakis, Konstantinos; Eleftherakis, Panagiotis-Eleftherios; Xydis, Sotirios; Soudris, Dimitrios; Sorensen, Tyler; Campanoni, Simone; et al (June 2024, IEEE)

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EMISSARY: Enhanced Miss Awareness Replacement Policy for L2 Instruction Caching

https://doi.org/10.1145/3579371.3589097

Nagendra, Nayana Prasad; Godala, Bhargav Reddy; Chaturvedi, Ishita; Patel, Atmn; Kanev, Svilen; Moseley, Tipp; Stark, Jared; Pokam, Gilles A.; Campanoni, Simone; August, David I. (June 2023, Proceedings of the 50th International Symposium on Computer Architecture (ISCA))

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NOELLE Offers Empowering LLVM Extensions

https://doi.org/10.1109/CGO53902.2022.9741276

Matni, Angelo; Deiana, Enrico Armenio; Su, Yian; Gross, Lukas; Ghosh, Souradip; Apostolakis, Sotiris; Xu, Ziyang; Tan, Zujun; Chaturvedi, Ishita; Homerding, Brian; et al (April 2022, 2022 IEEE/ACM International Symposium on Code Generation and Optimization (CGO))

Modern and emerging architectures demand increasingly complex compiler analyses and transformations. As the emphasis on compiler infrastructure moves beyond support for peephole optimizations and the extraction of instruction-level parallelism, compilers should support custom tools designed to meet these demands with higher-level analysis-powered abstractions and functionalities of wider program scope. This paper introduces NOELLE, a robust open-source domain-independent compilation layer built upon LLVM providing this support. NOELLE extends abstractions and functionalities provided by LLVM enabling advanced, program-wide code analyses and transformations. This paper shows the power of NOELLE by presenting a diverse set of 11 custom tools built upon it.
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