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cs.CV2025
Using MLIR Transform to Design Sliced Convolution Algorithm
Victor Ferrari, Marcio Pereira, Lucas Alvarenga +2
This paper proposes SConvTransform, a Transform dialect extension that provides operations for optimizing 2D convolutions in MLIR. Its main operation, SConvOp, lowers Linalg convol…
cs.CV2024
ConvBench: A Comprehensive Benchmark for 2D Convolution Primitive Evaluation
Lucas Alvarenga, Victor Ferrari, Rafael Souza +2
Convolution is a compute-intensive operation placed at the heart of Convolution Neural Networks (CNNs). It has led to the development of many high-performance algorithms, such as I…
cs.CV2023
Advancing Direct Convolution using Convolution Slicing Optimization and ISA Extensions
Victor Ferrari, Rafael Sousa, Marcio Pereira +4
Convolution is one of the most computationally intensive operations that must be performed for machine-learning model inference. A traditional approach to compute convolutions is k…