The Sparse Tensor Algebra Compiler Information Guide

  1. Overview on The Sparse Tensor Algebra Compiler
  2. Core Information
  3. Recent Updates
  4. Expert Insights
  5. Summary

Overview on The Sparse Tensor Algebra Compiler

The Sparse Tensor Algebra Compiler Guide
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Core Information

MLIR Open Meeting 2022-02-10: PyTACO - An End-to-End Use Case for the Sparse Tensor Compiler News
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Recent Updates

Full The TACO Sparse Tensor Algebra Compiler News
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[OOPSLA] Compilation of Dynamic Sparse Tensor Algebra
[OOPSLA] Compilation of Dynamic Sparse Tensor Algebra
Format Abstraction for Sparse Tensor Algebra Compilers
Format Abstraction for Sparse Tensor Algebra Compilers
2021 LLVM Dev Mtg “Sparse Tensor Algebra Optimizations in MLIR”
2021 LLVM Dev Mtg “Sparse Tensor Algebra Optimizations in MLIR”
A Sparse Iteration Space Transformation Framework for Sparse Tensor Algebra
A Sparse Iteration Space Transformation Framework for Sparse Tensor Algebra
ICPP Keynote: Making Sparse Fast with the TACO Domain Specific Language for Sparse Tensor Algebra
ICPP Keynote: Making Sparse Fast with the TACO Domain Specific Language for Sparse Tensor Algebra
The Tensor Algebra Compiler
The Tensor Algebra Compiler
taco: A Tool to Generate Tensor Algebra Kernels
taco: A Tool to Generate Tensor Algebra Kernels
DISTAL: The Distributed Tensor Algebra Compiler
DISTAL: The Distributed Tensor Algebra Compiler
Rohan Yadav: DISTAL, The Distributed Tensor Algebra Compiler
Rohan Yadav: DISTAL, The Distributed Tensor Algebra Compiler
Tailors: Accelerating Sparse Tensor Algebra by Overbooking Buffer Occupancy @ MICRO 2023
Tailors: Accelerating Sparse Tensor Algebra by Overbooking Buffer Occupancy @ MICRO 2023
Brief Announcement: Sparse Tensor Transpositions
Brief Announcement: Sparse Tensor Transpositions

Expert Insights

Data is compiled from public records and verified media reports.

Last Updated: September 29, 2026

Summary

Information The Tensor Algebra Compiler Guide
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Summary

Bixia Zheng‎ will talk about the MLIR-PyTACO bridge, which connects the PyTACO DSL to the MLIR Presented at GPCE 2018 Achieving high performance is no easy task. When it comes to program operating on Fredrik Kjolstad, Shoaib Kamil, Stephen Chou, David Lugato, Saman Amarasinghe Many applications, from social network graph analytics to control flow analysis, compute on Paper: dl.acm.org/citation.cfm?id=3276493 This paper shows how to build 2021 LLVM Developers' Meeting llvm.org/devmtg/2021-11/ — Automatic generation of high-performance pldi22.sigplan.org/details/pldi-2022-pldi/12/DISTAL-The-Distributed- Z. Y. Xue, Y. N. Wu, J. S. Emer, V. Sze, "Tailors: Accelerating

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