Search Results for author: Mohammad Sadrosadati

Found 3 papers, 2 papers with code

TargetCall: Eliminating the Wasted Computation in Basecalling via Pre-Basecalling Filtering

1 code implementation9 Dec 2022 Meryem Banu Cavlak, Gagandeep Singh, Mohammed Alser, Can Firtina, Joël Lindegger, Mohammad Sadrosadati, Nika Mansouri Ghiasi, Can Alkan, Onur Mutlu

However, for many applications, the majority of reads do no match the reference genome of interest (i. e., target reference) and thus are discarded in later steps in the genomics pipeline, wasting the basecalling computation.

Hermes: Accelerating Long-Latency Load Requests via Perceptron-Based Off-Chip Load Prediction

1 code implementation1 Sep 2022 Rahul Bera, Konstantinos Kanellopoulos, Shankar Balachandran, David Novo, Ataberk Olgun, Mohammad Sadrosadati, Onur Mutlu

To this end, we propose a new technique called Hermes, whose key idea is to: 1) accurately predict which load requests might go off-chip, and 2) speculatively fetch the data required by the predicted off-chip loads directly from the main memory, while also concurrently accessing the cache hierarchy for such loads.

ORIGAMI: A Heterogeneous Split Architecture for In-Memory Acceleration of Learning

no code implementations30 Dec 2018 Hajar Falahati, Pejman Lotfi-Kamran, Mohammad Sadrosadati, Hamid Sarbazi-Azad

To utilize available bandwidth without violating area and power budgets of logic layer, ORIGAMI comes with a computation-splitting compiler that divides an ML algorithm between in-memory accelerators and an out-of-the-memory platform in a balanced way and with minimum inter-communications.

Cannot find the paper you are looking for? You can Submit a new open access paper.