Search Results for author: Ataberk Olgun

Found 2 papers, 1 papers with code

Analysis of Distributed Optimization Algorithms on a Real Processing-In-Memory System

no code implementations10 Apr 2024 Steve Rhyner, Haocong Luo, Juan Gómez-Luna, Mohammad Sadrosadati, Jiawei Jiang, Ataberk Olgun, Harshita Gupta, Ce Zhang, Onur Mutlu

Processor-centric architectures (e. g., CPU, GPU) commonly used for modern ML training workloads are limited by the data movement bottleneck, i. e., due to repeatedly accessing the training dataset.

Distributed Optimization

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.

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