21 citations · 26 across the 5 of their papers we have counts for
5 papers
An Open-Source ML-Based Full-Stack Optimization Framework for Machine Learning Accelerators
Hadi Esmaeilzadeh, Soroush Ghodrati, Andrew B. Kahng +8
Parameterizable machine learning (ML) accelerators are the product of recent breakthroughs in ML. To fully enable their design space exploration (DSE), we propose a physical-design…
Performance Analysis of DNN Inference/Training with Convolution and non-Convolution Operations
Hadi Esmaeilzadeh, Soroush Ghodrati, Andrew B. Kahng +4
Today's performance analysis frameworks for deep learning accelerators suffer from two significant limitations. First, although modern convolutional neural network (CNNs) consist o…
GNNIE: GNN Inference Engine with Load-balancing and Graph-Specific Caching
Sudipta Mondal, Susmita Dey Manasi, Kishor Kunal +2
Graph neural networks (GNN) analysis engines are vital for real-world problems that use large graph models. Challenges for a GNN hardware platform include the ability to (a) host a…
NeuPart: Using Analytical Models to Drive Energy-Efficient Partitioning of CNN Computations on Cloud-Connected Mobile Clients
Susmita Dey Manasi, Farhana Sharmin Snigdha, Sachin S. Sapatnekar
Data processing on convolutional neural networks (CNNs) places a heavy burden on energy-constrained mobile platforms. This work optimizes energy on a mobile client by partitioning…
Straintronic magneto-tunneling-junction based ternary content addressable memory
S. Dey Manasi, M. M. Al Rashid, J. Atulasimha +2
Straintronic magneto-tunneling junction (s-MTJ) switches, whose resistances are controlled with voltage-generated strain in the magnetostrictive free layer of the MTJ, are extremel…