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Mohammad Alian

Researcher at University of Illinois at Urbana–Champaign

Publications -  19
Citations -  473

Mohammad Alian is an academic researcher from University of Illinois at Urbana–Champaign. The author has contributed to research in topics: Server & Network interface. The author has an hindex of 9, co-authored 19 publications receiving 235 citations. Previous affiliations of Mohammad Alian include University of Kansas.

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The gem5 Simulator: Version 20.0+

Jason Lowe-Power, +78 more
TL;DR: How the gem5 simulator has transitioned to a formal governance model to enable continued improvement and community support for the next 20 years of computer architecture research is discussed.
Proceedings ArticleDOI

A network-centric hardware/algorithm co-design to accelerate distributed training of deep neural networks

TL;DR: This paper sets out to reduce this significant communication cost by embedding data compression accelerators in the Network Interface Cards (NICs) and proposes an aggregator-free training algorithm that exchanges gradients in both legs of communication in the group, while the workers collectively perform the aggregation in a distributed manner.
Proceedings ArticleDOI

Planaria: Dynamic Architecture Fission for Spatial Multi-Tenant Acceleration of Deep Neural Networks

TL;DR: This paper defines Planaria1, a microarchitectural capability that can dynamically fission (break) into multiple smaller yet full-fledged DNN engines at runtime that enables spatially co-locating multiple DNN inference services on the same hardware, offering simultaneous multi-tenant DNN acceleration.
Proceedings ArticleDOI

Flashshare: punching through server storage stack from kernel to firmware for ultra-low latency SSDs

TL;DR: FLASHSHARE is a holistic cross-stack approach, which can significantly reduce I/O interferences among co-running applications at a server without any change in applications, and can shorten the average and 99th-percentile turnaround response times of co- running applications by 22% and 31%, respectively.
Proceedings ArticleDOI

Application-transparent near-memory processing architecture with memory channel network

TL;DR: Memory Channel Network can serve as an application-transparent framework which can seamlessly unify near-memory processing within a server and distributed computing across such servers for data-intensive applications.