1 citations · 1 across the 3 of their papers we have counts for
5 papers
SafeBet: Secure, Simple, and Fast Speculative Execution
Conor Green, Cole Nelson, Mithuna Thottethodi +1
Spectre attacks exploit microprocessor speculative execution to read and transmit forbidden data outside the attacker's trust domain and sandbox. Recent hardware schemes allow pote…
OCCAM: Optimal Data Reuse for Convolutional Neural Networks
Ashish Gondimalla, Jianqiao Liu, T. N. Vijaykumar +1
Convolutional neural networks (CNNs) are emerging as powerful tools for image processing in important commercial applications. We focus on the important problem of improving the la…
Barrier-Free Large-Scale Sparse Tensor Accelerator (BARISTA) For Convolutional Neural Networks
Ashish Gondimalla, Sree Charan Gundabolu, T. N. Vijaykumar +1
Convolutional neural networks (CNNs) are emerging as powerful tools for visual recognition. Recent architecture proposals for sparse CNNs exploit zeros in the feature maps and filt…
Booster: An Accelerator for Gradient Boosting Decision Trees
Mingxuan He, T. N. Vijaykumar, Mithuna Thottethodi
We propose Booster, a novel accelerator for gradient boosting trees based on the unique characteristics of gradient boosting models. We observe that the dominant steps of gradient…
Dart: Divide and Specialize for Fast Response to Congestion in RDMA-based Datacenter Networks
Jiachen Xue, Muhammad Usama Chaudhry, Balajee Vamanan +2
Though Remote Direct Memory Access (RDMA) promises to reduce datacenter network latencies significantly compared to TCP (e.g., 10x), end-to-end congestion control in the presence o…