Olatunji Ruwase
Olatunji Ruwase
Microsoft Research
Verified email at - Homepage
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Bloom: A 176b-parameter open-access multilingual language model
T Le Scao, A Fan, C Akiki, E Pavlick, S Ilić, D Hesslow, R Castagné, ...
Zero: Memory optimizations toward training trillion parameter models
S Rajbhandari, J Rasley, O Ruwase, Y He
SC20: International Conference for High Performance Computing, Networking …, 2020
Deepspeed: System optimizations enable training deep learning models with over 100 billion parameters
J Rasley, S Rajbhandari, O Ruwase, Y He
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020
A Practical Dynamic Buffer Overflow Detector.
O Ruwase, MS Lam
NDSS 2004, 159-169, 2004
Accelerating deep convolutional neural networks using specialized hardware
K Ovtcharov, O Ruwase, JY Kim, J Fowers, K Strauss, ES Chung
Microsoft Research Whitepaper 2 (11), 1-4, 2015
{Zero-offload}: Democratizing {billion-scale} model training
J Ren, S Rajbhandari, RY Aminabadi, O Ruwase, S Yang, M Zhang, D Li, ...
2021 USENIX Annual Technical Conference (USENIX ATC 21), 551-564, 2021
Zero-infinity: Breaking the gpu memory wall for extreme scale deep learning
S Rajbhandari, O Ruwase, J Rasley, S Smith, Y He
Proceedings of the international conference for high performance computing …, 2021
Flexible hardware acceleration for instruction-grain program monitoring
S Chen, M Kozuch, T Strigkos, B Falsafi, PB Gibbons, TC Mowry, ...
ACM SIGARCH Computer Architecture News 36 (3), 377-388, 2008
Deepspeed-inference: enabling efficient inference of transformer models at unprecedented scale
RY Aminabadi, S Rajbhandari, AA Awan, C Li, D Li, E Zheng, O Ruwase, ...
SC22: International Conference for High Performance Computing, Networking …, 2022
Performance modeling and scalability optimization of distributed deep learning systems
F Yan, O Ruwase, Y He, T Chilimbi
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge …, 2015
Parallelizing dynamic information flow tracking
O Ruwase, PB Gibbons, TC Mowry, V Ramachandran, S Chen, M Kozuch, ...
Proceedings of the twentieth annual symposium on Parallelism in algorithms …, 2008
Toward accelerating deep learning at scale using specialized hardware in the datacenter
K Ovtcharov, O Ruwase, JY Kim, J Fowers, K Strauss, ES Chung
2015 IEEE Hot Chips 27 Symposium (HCS), 1-38, 2015
Ditto: a system for opportunistic caching in multi-hop wireless networks
FR Dogar, A Phanishayee, H Pucha, O Ruwase, DG Andersen
Proceedings of the 14th ACM international conference on Mobile computing and …, 2008
Hyperdrive: Exploring hyperparameters with pop scheduling
J Rasley, Y He, F Yan, O Ruwase, R Fonseca
Proceedings of the 18th ACM/IFIP/USENIX Middleware Conference, 1-13, 2017
Page overlays: An enhanced virtual memory framework to enable fine-grained memory management
V Seshadri, G Pekhimenko, O Ruwase, O Mutlu, PB Gibbons, MA Kozuch, ...
ACM SIGARCH Computer Architecture News 43 (3S), 79-91, 2015
Phi-3 technical report: A highly capable language model locally on your phone
M Abdin, SA Jacobs, AA Awan, J Aneja, A Awadallah, H Awadalla, ...
arXiv preprint arXiv:2404.14219, 2024
Neural network training performance optimization framework
TA Chilimbi, O Ruwase, S Rajbhandari, M Carbin, Y He
US Patent App. 14/986,186, 2017
Deepspeed-chat: Easy, fast and affordable rlhf training of chatgpt-like models at all scales
Z Yao, RY Aminabadi, O Ruwase, S Rajbhandari, X Wu, AA Awan, ...
arXiv preprint arXiv:2308.01320, 2023
SERF: Efficient scheduling for fast deep neural network serving via judicious parallelism
F Yan, O Ruwase, Y He, E Smirni
SC'16: Proceedings of the International Conference for High Performance …, 2016
Decoupled lifeguards: enabling path optimizations for dynamic correctness checking tools
O Ruwase, S Chen, PB Gibbons, TC Mowry
Proceedings of the 2010 ACM SIGPLAN conference on Programming language …, 2010
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