From the 1 of 5 linked papers with an AI index.
5 papers
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…
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…
HaShiFlex: A High-Throughput Hardened Shifter DNN Accelerator with Fine-Tuning Flexibility
Jonathan Herbst, Michael Pellauer, Sherief Reda
We introduce a high-throughput neural network accelerator that embeds most network layers directly in hardware, minimizing data transfer and memory usage while preserving a degree…
CELLO: Co-designing Schedule and Hybrid Implicit/Explicit Buffer for Complex Tensor Reuse
Raveesh Garg, Michael Pellauer, Sivasankaran Rajamanickam +1
Tensor algebra accelerators have been gaining popularity for running high-performance computing (HPC) workloads. Identifying optimal schedules for individual tensor operations and…
HARP: A Taxonomy for Heterogeneous and Hierarchical Processors for Mixed-reuse Workloads
Raveesh Garg, Michael Pellauer, Tushar Krishna
Artificial intelligence (AI) application domains consist of a mix of tensor operations with high and low arithmetic intensities (aka reuse). Hierarchical (i.e. compute along multip…