19 citations · 29 across the 6 of their papers we have counts for
6 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
We present campaign diagrams, a visualization technique for phase-level analysis of resource utilization and bottlenecks in modern workloads. Existing tools have a trade-off: roofl…
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…
FuseMax: Leveraging Extended Einsums to Optimize Attention Accelerator Design
Nandeeka Nayak, Xinrui Wu, Toluwanimi O. Odemuyiwa +3
Attention for transformers is a critical workload that has recently received significant "attention" as a target for custom acceleration. Yet, while prior work succeeds in reducing…
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…
TeAAL: A Declarative Framework for Modeling Sparse Tensor Accelerators
Nandeeka Nayak, Toluwanimi O. Odemuyiwa, Shubham Ugare +3
Over the past few years, the explosion in sparse tensor algebra workloads has led to a corresponding rise in domain-specific accelerators to service them. Due to the irregularity p…