Fredrik Kjolstad
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Assistant Professor Department of Computer Science Stanford University Office: Gates 486 kjolstad@stanford.edu CV |
I aim to make it easy to program sparse computing applications that can run everywhere with end-to-end performance that matches or exceeds the best hand-optimized codes. A sparse application computes on a system where most parts do not interact—they are sparsely interconnected. Examples include sparse matrices, meshes, and graphical arrangements used to simulate the dynamics of robots, optimize the flow of traffic, compute the rank of web pages, estimate the similarity of genome loci, or train sparse deep neural networks. Sparse computing is ubiquitous and will become increasingly important with the growth of robotic and autonomous vehicle applications, data analytics, and machine learning.
I have developed the taco compiler for computing sparse tensor expressions and the Simit programming language for computing on sparse systems. My broad research interests include compilers, programming models and languages, parallel computing, software engineering, and performance engineering.
My thesis on Sparse Tensor Algebra Compilation is the best place to start reading about the ideas behind the tensor algebra compiler (taco) and sparse iteration model.
PhD Students
- James Dong
- Olivia Hsu (with Kunle Olukotun)
- Scott Kovach
- Rubens Lacouture (with Kunle Olukotun)
- Alexander Root
- Shiv Sundram
- Haoran Xu
- Rohan Yadav (with Alex Aiken)
- Bobby Yan
Publications
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Compiling Recurrences over Dense and Sparse Arrays Shiv Sundram, Muhammad Usman Tariq, and Fredrik Kjolstad Proceedings of the ACM on Programming Languages (accepted), Volume 8, Issue OOPSLA, October 2024 |
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Compilation of Modular and General Sparse Workspaces Genghan Zhang, Olivia Hsu, and Fredrik Kjolstad Proceedings of the ACM on Programming Languages (accepted), Volume 8, Issue PLDI, June 2024 |
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BaCO: A Fast and Portable Bayesian Compiler Optimization Framework Erik Hellsten, Artur Souza, Johannes Lenfers, Rubens Lacouture, Olivia Hsu, Adel Ejjeh, Fredrik Kjolstad, Michel Steuwer, Kunle Olukotun, and Luigi Nardi International Conference on Architectural Support for Programming Languages and Operating Systems (accepted) (ASPLOS), April 2024 |
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Revet: A Language and Compiler for Dataflow Threads Alexander Rucker, Shiv Sundram, Coleman Smith, Matt Vilim, Raghu Prabhakar, Fredrik Kjolstad, and Kunle Olukotun IEEE International Symposium on High-Performance Computer Architecture (HPCA), March 2024 |
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Legate Sparse: Distributed Sparse Computing in Python Rohan Yadav, Wonchan Lee, Melih Elibol, Manolis Papadakis, Taylor Lee-Patti, Michael Garland, Alex Aiken, Fredrik Kjolstad, and Michael Bauer ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis (SC), November 2023 |
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Indexed Streams: A Formal Intermediate Representation for the Fused Execution of Contraction Operations Scott Kovach, Praneeth Kolichala, Timothy Gu, and Fredrik Kjolstad Proceedings of the ACM on Programming Languages, Volume 7, Issue PLDI, June 2023 |
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Mosaic: An Interoperable Compiler for Tensor Algebra Manya Bansal, Olivia Hsu, Kunle Olukotun, and Fredrik Kjolstad Proceedings of the ACM on Programming Languages, Volume 7, Issue PLDI, June 2023 Distinguished Paper Award |
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The Sparse Abstract Machine Olivia Hsu, Maxwell Strange, Ritvik Sharma, Jaeyeon Won, Kunle Olukotun, Joel Emer, Mark Horowitz, and Fredrik Kjolstad Architectural Support for Programming Languages and Operating Systems (ASPLOS), March 2023 |
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Unified Buffer: Compiling Image Processing and Machine Learning Applications to Push-Memory Accelerators Qiaoyi Liu, Jeff Setter, Dillon Huff, Maxwell Strange, Kathleen Feng, Mark Horowitz, Priyanka Raina, and Fredrik Kjolstad ACM Transactions on Architecture and Code Optimization (TACO), March 2023 |
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Looplets: A Language For Structured Coiteration Willow Ahrens, Daniel Donenfeld, Fredrik Kjolstad, and Saman Amarasinghe International Symposium on Code Generation and Optimization (CGO), February 2023 |
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AHA: An agile approach to the design of coarse-grained reconfigurable accelerators and compilers Kalhan Koul, Jackson Melchert, Kavya Sreedhar, Leonard Truong, Gedeon Nyengele, Keyi Zhang, Qiaoyi Liu, Jeff Setter, Po-Han Chen, Yuchen Mei, Maxwell Strange, Ross Daly, Caleb Donovick, Alex Carsello, Taeyoung Kong, Kathleen Feng, Dillon Huff, Ankita Nayak, Raj Setaluri, James Thomas, Nikhil Bhagdikar, David Durst, Zachary Myers, Nestan Tsiskaridze, Stephen Richardson, Rick Bahr, Kayvon Fatahalian, Pat Hanrahan, Clark Barrett, Mark Horowitz, Christopher Torng, Fredrik Kjolstad, and Priyanka Raina ACM Transactions on Embedded Computing Systems (TECS), January 2023 |
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SpDISTAL: Compiling Distributed Sparse Tensor Computations Rohan Yadav, Alex Aiken, and Fredrik Kjolstad ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis (SC), November 2022 |
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Compiler Support for Sparse Tensor Computations in MLIR Aart J.C Bik, Penporn Koanantakool, Tatiana Shpeisman, Nicolas Vasilache, Bixia Zheng, and Fredrik Kjolstad ACM Transactions on Architecture and Code Optimization (TACO), September 2022 |
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DISTAL: The Distributed Tensor Algebra Compiler Rohan Yadav, Alex Aiken, and Fredrik Kjolstad ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), June 2022 |
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Autoscheduling for Sparse Tensor Algebra with an Asymptotic Cost Model Peter Ahrens, Fredrik Kjolstad, and Saman Amarasinghe ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), June 2022 |
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Copy-and-Patch Compilation Haoran Xu and Fredrik Kjolstad Proceedings of the ACM on Programming Languages, Volume 5, Issue OOPSLA, November 2021 Distinguished Paper Award |
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Compilation of Sparse Array Programming Models Rawn Henry, Olivia Hsu, Rohan Yadav, Stephen Chou, Kunle Olukotun, Saman Amarasinghe, and Fredrik Kjolstad Proceedings of the ACM on Programming Languages, Volume 5, Issue OOPSLA, November 2021 |
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A Sparse Iteration Space Transformation Framework for Sparse Tensor Algebra Ryan Senanayake, Changwan Hong, Ziheng Wang, Amalee Wilson, Stephen Chou, Shoaib Kamil, Saman Amarasinghe, and Fredrik Kjolstad Proceedings of the ACM on Programming Languages, Volume 4, Issue OOPSLA, November 2020 |
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Creating an Agile Hardware Design Flow Rick Bahr, Clark Barrett, Nikhil Bhagdikar, Alex Carsello, Ross Daly, Caleb Donovick, David Durst, Kayvon Fatahalian, Kathleen Feng, Pat Hanrahan, Teguh Hofstee, Mark Horowitz, Dillon Huff, Fredrik Kjolstad, Taeyoung Kong, Qiaoyi Liu, Makai Mann, Jackson Melchert, Ankita Nayak, Aina Niemetz, Gedeon Nyengele, Priyanka Raina, Stephen Richardson, Raj Setaluri, Jeff Setter, Kavya Sreedhar, Maxwell Strange, James Thomas, Christopher Torng, Leonard Truong, Nestan Tsiskaridze, and Keyi Zhang Design Automation Conference (DAC), July 2020 |
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Sparse Tensor Transpositions Suzanne Mueller, Peter Ahrens, Stephen Chou, Fredrik Kjolstad, and Saman Amarasinghe ACM Symposium on Parallelism in Algorithms and Architectures (SPAA brief announcement), July 2020 |
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Automatic Generation of Efficient Sparse Tensor Format Conversion Routines Stephen Chou, Fredrik Kjolstad, and Saman Amarasinghe ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI), June 2020 |
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Tensor Algebra Compilation with Workspaces Fredrik Kjolstad, Peter Ahrens, Shoaib Kamil, and Saman Amarasinghe International Symposium on Code Generation and Optimization (CGO), February 2019 |
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Format Abstraction for Sparse Tensor Algebra Compilers Stephen Chou, Fredrik Kjolstad, and Saman Amarasinghe Proceedings of the ACM on Programming Languages, Volume 2, Issue OOPSLA, October 2018 |
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Taco: compilation et génération de code d’expressions tensorielles David Lugato, Fredrik Kjolstad, Stephen Chou, Saman Amarasinghe, and Shoaib Kamil AVANCÉES, Volume 12, 2018 |
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taco: A Tool to Generate Tensor Algebra Kernels Fredrik Kjolstad, Stephen Chou, David Lugato, Shoaib Kamil, and Saman Amarasinghe 32th IEEE/ACM International Conference on Automated Software Engineering (ASE tools paper), November 2017 |
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The Tensor Algebra Compiler Fredrik Kjolstad, Shoaib Kamil, Stephen Chou, David Lugato, and Saman Amarasinghe Proceedings of the ACM on Programming Languages, Volume 1, Issue OOPSLA, October 2017 Distinguished Paper Award |
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Simit: A Language for Physical Simulation Fredrik Kjolstad, Shoaib Kamil, Jonathan Ragan-Kelley, David I. W. Levin, Shinjiro Sueda, Desai Chen, Etienne Vouga, Danny M. Kaufman, Gurtej Kanwar, Wojciech Matusik, and Saman Amarasinghe ACM Transactions on Graphics (TOG presented at SIGGRAPH 2016), May 2016 |
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Why New Programming Languages for Simulation? Gilbert Louis Bernstein and Fredrik Kjolstad ACM Transactions on Graphics (TOG perspective), May 2016 |
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MPI Datatype Processing using Runtime Compilation Timo Schneider, Fredrik Kjolstad, and Torsten Hoefler 20th European MPI Users' Group Meeting, September 2013 Best Paper Award |
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Automatic Datatype Generation and Optimization Fredrik Kjolstad, Torsten Hoefler, and Marc Snir 17th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming (PPoPP short paper), February 2012 |
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Transformation for Class Immutability Fredrik Kjolstad, Danny Dig, Gabriel Acevedo, and Marc Snir 33rd International Conference on Software Engineering (ICSE), May 2011 |
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Bringing the HPC Programmer's IDE into the 21st Century through Refactoring Fredrik Kjolstad, Danny Dig, and Marc Snir SPLASH 2010 Workshop on Concurrency for the Application Programmer, October 2010 |
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Ghost Cell Pattern Fredrik Kjolstad and Marc Snir 2nd Annual Workshop on Parallel Programming Patterns, March 2010 |
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