Fredrik Kjolstad

Assistant Professor
Department of Computer Science
Stanford University
Office: Gates 486 kjolstad@cs.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 theory.

PhD Students

James Dong
Olivia Hsu (with Kunle Olukotun)
Scott Kovach
Shiv Sundram
Haoran Xu
Rohan Yadav (with Alex Aiken)
Bobby Yan

Publications

Compiler Support for Sparse Tensor Computations in MLIR Aarti J.C Bik, Penporn Koanantakool, Tatiana Shpeisman, Nicolas Vasilache, Bixia Zheng, and Fredrik Kjolstad ACM Transactions on Architecture and Code Optimization (TACO), June 2022
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
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
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
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
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
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
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
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
Tensor Algebra Compilation with Workspaces Fredrik Kjolstad, Peter Ahrens, Shoaib Kamil, and Saman Amarasinghe International Symposium on Code Generation and Optimization (CGO), February 2019
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
Taco: compilation et génération de code d’expressions tensorielles David Lugato, Fredrik Kjolstad, Stephen Chou, Saman Amarasinghe, and Shoaib Kamil AVANCÉES, Volume 12, 2018
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
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
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
Why New Programming Languages for Simulation? Gilbert Louis Bernstein and Fredrik Kjolstad ACM Transactions on Graphics (TOG perspective), May 2016
MPI Datatype Processing using Runtime Compilation Timo Schneider, Fredrik Kjolstad, and Torsten Hoefler 20th European MPI Users' Group Meeting, September 2013 Best Paper Award
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
Transformation for Class Immutability Fredrik Kjolstad, Danny Dig, Gabriel Acevedo, and Marc Snir 33rd International Conference on Software Engineering (ICSE), May 2011
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
Ghost Cell Pattern Fredrik Kjolstad and Marc Snir 2nd Annual Workshop on Parallel Programming Patterns, March 2010