From the 1 of 10 linked papers with an AI index.
1 citations · 1 across the 6 of their papers we have counts for
10 papers
The Einsum-Enabled Design Space for Graph Algorithms: A BFS Case Study
Toluwanimi O. Odemuyiwa, Serban D. Porumbescu, Muhammad Osama +2
We propose a principled approach to reasoning about various graph algorithm implementations. We leverage the extended general Einsum notation (EDGE) which allows us to factor compl…
Campaign Diagrams: Visualizing the March Through the Phases of a Workload
Toluwanimi O. Odemuyiwa, John D. Owens, Michael Pellauer +1
The paper introduces campaign diagrams, a visualization technique that displays compute throughput, memory bandwidth, traffic volume, and latency across the phases of a workload to…
The EDGE Language: Extended General Einsums for Graph Algorithms
Toluwanimi O. Odemuyiwa, Serban D. Porumbescu, Nandeeka Nayak +3
In this work, we propose a unified abstraction for graph algorithms: the Extended General Einsums language, or EDGE. The EDGE language expresses graph algorithms in the language of…
The Turbo-Charged Mapper: Fast and Optimal Mapping for Energy-efficient and Low-latency Accelerator Design
Michael Gilbert, Tanner Andrulis, Vivienne Sze +1
The energy and latency of an accelerator running a deep neural network (DNN) depend on how the computation and data movement are scheduled in the accelerator (i.e., mapping), and p…
Fast and Fusiest: An Optimal Fusion-Aware Mapper for Accelerator Design
Tanner Andrulis, Michael Gilbert, Vivienne Sze +1
A low-latency and energy-efficient tensor algebra accelerator design must optimize how data movement and operations are scheduled (i.e., mapped) in the accelerator architecture. A…
Mambalaya: Einsum-Based Fusion Optimizations on State-Space Models
Toluwanimi O. Odemuyiwa, John D. Owens, Joel S. Emer +1
Mamba is an emerging, complex workload with various short-range and long-range dependencies, nonlinearities, and elementwise computations that are unable to run at near-peak speeds…