Search Results for author: Babak Falsafi

Found 4 papers, 2 papers with code

Accuracy Boosters: Epoch-Driven Mixed-Mantissa Block Floating-Point for DNN Training

no code implementations19 Nov 2022 Simla Burcu Harma, Ayan Chakraborty, Babak Falsafi, Martin Jaggi, Yunho Oh

The unprecedented growth in DNN model complexity, size, and amount of training data has led to a commensurate increase in demand for computing and a search for minimal encoding.

Scale-out Systolic Arrays

1 code implementation22 Mar 2022 Ahmet Caner Yüzügüler, Canberk Sönmez, Mario Drumond, Yunho Oh, Babak Falsafi, Pascal Frossard

In this work, we study three key pillars in multi-pod systolic array designs, namely array granularity, interconnect, and tiling.

SMoTherSpectre: exploiting speculative execution through port contention

3 code implementations5 Mar 2019 Atri Bhattacharyya, Alexandra Sandulescu, Matthias Neugschwandtner, Alessandro Sorniotti, Babak Falsafi, Mathias Payer, Anil Kurmus

Spectre, Meltdown, and related attacks have demonstrated that kernels, hypervisors, trusted execution environments, and browsers are prone to information disclosure through micro-architectural weaknesses.

Cryptography and Security

Training DNNs with Hybrid Block Floating Point

no code implementations NeurIPS 2018 Mario Drumond, Tao Lin, Martin Jaggi, Babak Falsafi

We identify block floating point (BFP) as a promising alternative representation since it exhibits wide dynamic range and enables the majority of DNN operations to be performed with fixed-point logic.

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