109 citations · 616 across the 40 of their papers we have counts for
5 papers · 1 filter
Serving Recurrent Neural Networks Efficiently with a Spatial Accelerator
Tian Zhao, Yaqi Zhang, Kunle Olukotun
Recurrent Neural Network (RNN) applications form a major class of AI-powered, low-latency data center workloads. Most execution models for RNN acceleration break computation graphs…
Efficient Multiway Hash Join on Reconfigurable Hardware
Kunle Olukotun, Raghu Prabhakar, Rekha Singhal +2
We propose the algorithms for performing multiway joins using a new type of coarse grain reconfigurable hardware accelerator~-- ``Plasticine''~-- that, compared with other accelera…
Polystore++: Accelerated Polystore System for Heterogeneous Workloads
Rekha Singhal, Nathan Zhang, Luigi Nardi +2
Modern real-time business analytic consist of heterogeneous workloads (e.g, database queries, graph processing, and machine learning). These analytic applications need programming…
DeepFreak: Learning Crystallography Diffraction Patterns with Automated Machine Learning
Artur Souza, Leonardo B. Oliveira, Sabine Hollatz +5
Serial crystallography is the field of science that studies the structure and properties of crystals via diffraction patterns. In this paper, we introduce a new serial crystallogra…
MLSys: The New Frontier of Machine Learning Systems
Alexander Ratner, Dan Alistarh, Gustavo Alonso +66
Machine learning (ML) techniques are enjoying rapidly increasing adoption. However, designing and implementing the systems that support ML models in real-world deployments remains…