Fast Reader Notes: We need new intermediate representations that break up today's monolithic and inflexible machine learning kernels into more ... Gus Smith presents the results of his work on “ML-Driven Auto-Configurator for Sparse

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We need new intermediate representations that break up today's monolithic and inflexible machine learning kernels into more ... Gus Smith presents the results of his work on “ML-Driven Auto-Configurator for Sparse

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  • Gus Smith presents the results of his work on “ML-Driven Auto-Configurator for Sparse
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Context Images

MLIR Open Meeting 2021-08-26: High Performance GPU Tensor CoreCode Generation for Matmul Using MLIR
MLIR Open Meeting 2021-9-9: ML-Driven Auto-Configurator for Sparse Tensor Kernels
2025 EuroLLVM - An Introduction to Tensor Tiling in MLIR
MLIR Open Meeting 2021-10-28: Discussion on representing tiling on tensors + parallelism
2023 EuroLLVM - MLIR-based offline memory planning and other graph-level optimizations for xcore.ai
Open MLIR Meeting 10-13-2022: Discussion about broadcasting in TCP (Tensor Compute Primitives)
MLIR Open Meeting 2021-07-22: MLIR Data Visualization
2023 LLVM Dev Mtg - Optimization of CUDA GPU Kernels and Translation to AMDGPU in 4) Polygeist/MLIR
2021 LLVM Dev Mtg “Sparse Tensor Algebra Optimizations in MLIR”
RISE A functional pattern-based language in MLIR
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MLIR Open Meeting 2021-08-26: High Performance GPU Tensor CoreCode Generation for Matmul Using MLIR

MLIR Open Meeting 2021-08-26: High Performance GPU Tensor CoreCode Generation for Matmul Using MLIR

Read more details and related context about MLIR Open Meeting 2021-08-26: High Performance GPU Tensor CoreCode Generation for Matmul Using MLIR.

MLIR Open Meeting 2021-9-9: ML-Driven Auto-Configurator for Sparse Tensor Kernels

MLIR Open Meeting 2021-9-9: ML-Driven Auto-Configurator for Sparse Tensor Kernels

Gus Smith presents the results of his work on “ML-Driven Auto-Configurator for Sparse

2025 EuroLLVM - An Introduction to Tensor Tiling in MLIR

2025 EuroLLVM - An Introduction to Tensor Tiling in MLIR

Read more details and related context about 2025 EuroLLVM - An Introduction to Tensor Tiling in MLIR.

MLIR Open Meeting 2021-10-28: Discussion on representing tiling on tensors + parallelism

MLIR Open Meeting 2021-10-28: Discussion on representing tiling on tensors + parallelism

Read more details and related context about MLIR Open Meeting 2021-10-28: Discussion on representing tiling on tensors + parallelism.

2023 EuroLLVM - MLIR-based offline memory planning and other graph-level optimizations for xcore.ai

2023 EuroLLVM - MLIR-based offline memory planning and other graph-level optimizations for xcore.ai

Read more details and related context about 2023 EuroLLVM - MLIR-based offline memory planning and other graph-level optimizations for xcore.ai.

Open MLIR Meeting 10-13-2022: Discussion about broadcasting in TCP (Tensor Compute Primitives)

Open MLIR Meeting 10-13-2022: Discussion about broadcasting in TCP (Tensor Compute Primitives)

Read more details and related context about Open MLIR Meeting 10-13-2022: Discussion about broadcasting in TCP (Tensor Compute Primitives).

MLIR Open Meeting 2021-07-22: MLIR Data Visualization

MLIR Open Meeting 2021-07-22: MLIR Data Visualization

Read more details and related context about MLIR Open Meeting 2021-07-22: MLIR Data Visualization.

2023 LLVM Dev Mtg - Optimization of CUDA GPU Kernels and Translation to AMDGPU in 4) Polygeist/MLIR

2023 LLVM Dev Mtg - Optimization of CUDA GPU Kernels and Translation to AMDGPU in 4) Polygeist/MLIR

Read more details and related context about 2023 LLVM Dev Mtg - Optimization of CUDA GPU Kernels and Translation to AMDGPU in 4) Polygeist/MLIR.

2021 LLVM Dev Mtg “Sparse Tensor Algebra Optimizations in MLIR”

2021 LLVM Dev Mtg “Sparse Tensor Algebra Optimizations in MLIR”

Read more details and related context about 2021 LLVM Dev Mtg “Sparse Tensor Algebra Optimizations in MLIR”.

RISE A functional pattern-based language in MLIR

RISE A functional pattern-based language in MLIR

We need new intermediate representations that break up today's monolithic and inflexible machine learning kernels into more ...