5 papers
Accelerating Gradient-based Meta Learner
Varad Pimpalkhute, Amey Pandit, Mayank Mishra +1
Meta Learning has been in focus in recent years due to the meta-learner model's ability to adapt well and generalize to new tasks, thus, reducing both the time and data requirement…
Experience with PCIe streaming on FPGA for high throughput ML inferencing
Piyush Manavar, Manoj Nambiar, Nupur Sumeet +3
Achieving maximum possible rate of inferencing with minimum hardware resources plays a major role in reducing enterprise operational costs. In this paper we explore use of PCIe str…
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…
Fast Online "Next Best Offers" using Deep Learning
Rekha Singhal, Gautam Shroff, Mukund Kumar +5
In this paper, we present iPrescribe, a scalable low-latency architecture for recommending 'next-best-offers' in an online setting. The paper presents the design of iPrescribe and…
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…