3 papers
cs.DC2026
LP-GEMM: Integrating Layout Propagation into GEMM Operations
César Guedes Carneiro, Lucas Alvarenga, Guido Araujo +1
In Scientific Computing and modern Machine Learning (ML) workloads, sequences of dependent General Matrix Multiplications (GEMMs) often dominate execution time. While state-of-the-…
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…