Search Results - "General AND reference Cross-computing tools AND techniques Performance"

MLPerf Inference Benchmark by Reddi, Vijay Janapa, Cheng, Christine, Kanter, David, Mattson, Peter, Schmuelling, Guenther, Wu, Carole-Jean, Anderson, Brian, Breughe, Maximilien, Charlebois, Mark, Chou, William, Chukka, Ramesh, Coleman, Cody, Davis, Sam, Deng, Pan, Diamos, Greg, Duke, Jared, Fick, Dave, Gardner, J. Scott, Hubara, Itay, Idgunji, Sachin, Jablin, Thomas B., Jiao, Jeff, John, Tom St, Kanwar, Pankaj, Lee, David, Liao, Jeffery, Lokhmotov, Anton, Massa, Francisco, Meng, Peng, Micikevicius, Paulius, Osborne, Colin, Pekhimenko, Gennady, Rajan, Arun Tejusve Raghunath, Sequeira, Dilip, Sirasao, Ashish, Sun, Fei, Tang, Hanlin, Thomson, Michael, Wei, Frank, Wu, Ephrem, Xu, Lingjie, Yamada, Koichi, Yu, Bing, Yuan, George, Zhong, Aaron, Zhang, Peizhao, Zhou, Yuchen

“…Machine-learning (ML) hardware and software system demand is burgeoning. Driven by ML applications, the number of different ML inference systems has exploded…”
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InvisiSpec: making speculative execution invisible in the cache hierarchy by Yan, Mengjia, Choi, Jiho, Skarlatos, Dimitrios, Morrison, Adam, Fletcher, Christopher W., Torrellas, Josep

“…Hardware speculation offers a major surface for micro-architectural covert and side channel attacks. Unfortunately, defending against speculative execution…”
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Profiling a warehouse-scale computer by Kanev, Svilen, Darago, Juan Pablo, Hazelwood, Kim, Ranganathan, Parthasarathy, Moseley, Tipp, Wei, Gu-Yeon, Brooks, David

“…With the increasing prevalence of warehouse-scale (WSC) and cloud computing, understanding the interactions of server applications with the underlying…”
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Neural Acceleration for General-Purpose Approximate Programs by Esmaeilzadeh, H., Sampson, A., Ceze, L., Burger, D.

“…This paper describes a learning-based approach to the acceleration of approximate programs. We describe the \emph{Parrot transformation}, a program…”
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GraFBoost: Using Accelerated Flash Storage for External Graph Analytics by Jun, Sang-Woo, Wright, Andy, Zhang, Sizhuo, Xu, Shuotao, Arvind

“…We describe GraFBoost, a flash-based architecture with hardware acceleration for external analytics of multi-terabyte graphs. We compare the performance of…”
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FireSim: FPGA-Accelerated Cycle-Exact Scale-Out System Simulation in the Public Cloud by Karandikar, Sagar, Mao, Howard, Kim, Donggyu, Biancolin, David, Amid, Alon, Lee, Dayeol, Pemberton, Nathan, Amaro, Emmanuel, Schmidt, Colin, Chopra, Aditya, Huang, Qijing, Kovacs, Kyle, Nikolic, Borivoje, Katz, Randy, Bachrach, Jonathan, Asanovic, Krste

“…We present FireSim, an open-source simulation platform that enables cycle-exact microarchitectural simulation of large scale-out clusters by combining…”
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FLIN: Enabling Fairness and Enhancing Performance in Modern NVMe Solid State Drives by Tavakkol, Arash, Sadrosadati, Mohammad, Ghose, Saugata, Kim, Jeremie, Luo, Yixin, Wang, Yaohua, Mansouri Ghiasi, Nika, Orosa, Lois, Gomez-Luna, Juan, Mutlu, Onur

“…Modern solid-state drives (SSDs) use new host-interface protocols, such as NVMe, to provide applications with fast access to storage. These new protocols make…”
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Bubble-up: Increasing utilization in modern warehouse scale computers via sensible co-locations by Mars, Jason, Lingjia Tang, Hundt, Robert, Skadron, Kevin, Soffa, Mary Lou

“…As much of the world's computing continues to move into the cloud, the overprovisioning of computing resources to ensure the performance isolation of…”
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Predicting defects using network analysis on dependency graphs by Zimmermann, T., Nagappan, N.

“…In software development, resources for quality assurance are limited by time and by cost. In order to allocate resources effectively, managers need to rely on…”
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Memristor based computation-in-memory architecture for data-intensive applications by Hamdioui, Said, Xie, Lei, Du Nguyen, Hoang Anh, Taouil, Mottaqiallah, Bertels, Koen, Corporaal, Henk, Jiao, Hailong, Catthoor, Francky, Wouters, Dirk, Eike, Linn, van Lunteren, Jan

“…One of the most critical challenges for today's and future data-intensive and big-data problems is data storage and analysis. This paper first highlights some…”
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Flip-N-Write: a simple deterministic technique to improve PRAM write performance, energy and endurance by Cho, Sangyeun, Lee, Hyunjin

“…The phase-change random access memory (PRAM) technology is fast maturing to production levels. Main advantages of PRAM are non-volatility, byte addressability,…”
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DeftNN: addressing bottlenecks for DNN execution on GPUs via synapse vector elimination and near-compute data fission by Hill, Parker, Jain, Animesh, Hill, Mason, Zamirai, Babak, Hsu, Chang-Hong, Laurenzano, Michael A., Mahlke, Scott, Tang, Lingjia, Mars, Jason

“…Deep neural networks (DNNs) are key computational building blocks for emerging classes of web services that interact in real time with users via voice, images…”
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The influence of organizational structure on software quality: an empirical case study by Nagappan, Nachiappan, Murphy, Brendan, Basili, Victor

“…Often software systems are developed by organizations consisting of many teams of individuals working together. Brooks states in the Mythical Man Month book…”
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Amber: enabling precise full-system simulation with detailed modeling of all SSD resources by Gouk, Donghyun, Kwon, Miryeong, Zhang, Jie, Koh, Sungjoon, Choi, Wonil, Kim, Nam Sung, Kandemir, Mahmut, Jung, Myoungsoo

“…SSDs become a major storage component in modern memory hierarchies, and SSD research demands exploring future simulation-based studies by integrating SSD…”
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Energy Profiles of Java Collections Classes by Hasan, Samir, King, Zachary, Hafiz, Munawar, Sayagh, Mohammed, Adams, Bram, Hindle, Abram

“…We created detailed profiles of the energy consumed by common operations done on Java List, Map, and Set abstractions. The results show that the alternative…”
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Cross-architecture performance prediction (XAPP) using CPU code to predict GPU performance by Ardalani, Newsha, Lestourgeon, Clint, Sankaralingam, Karthikeyan, Xiaojin Zhu

“…GPUs have become prevalent and more general purpose, but GPU programming remains challenging and time consuming for the majority of programmers. In addition,…”
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DjiNN and Tonic: DNN as a service and its implications for future warehouse scale computers by Hauswald, Johann, Kang, Yiping, Laurenzano, Michael A., Chen, Quan, Li, Cheng, Mudge, Trevor, Dreslinski, Ronald G., Mars, Jason, Tang, Lingjia

“…As applications such as Apple Siri, Google Now, Microsoft Cortana, and Amazon Echo continue to gain traction, webservice companies are adopting large deep…”
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Rumba: An online quality management system for approximate computing by Khudia, Daya S, Zamirai, Babak, Samadi, Mehrzad, Mahlke, Scott

“…Approximate computing can be employed for an emerging class of applications from various domains such as multimedia, machine learning and computer vision. The…”
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SLEMI: Equivalence Modulo Input (EMI) Based Mutation of CPS Models for Finding Compiler Bugs in Simulink by Chowdhury, Shafiul Azam, Shrestha, Sohil Lal, Johnson, Taylor T., Csallner, Christoph

“…Finding bugs in commercial cyber-physical system development tools (or "model-based design" tools) such as MathWorks's Simulink is important in practice, as…”
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Application-transparent near-memory processing architecture with memory channel network by Alian, Mohammad, Min, Seung Won, Asgharimoghaddam, Hadi, Dhar, Ashutosh, Wang, Dong Kai, Roewer, Thomas, McPadden, Adam, O'Halloran, Oliver, Chen, Deming, Xiong, Jinjun, Kim, Daehoon, Hwu, Wen-mei, Kim, Nam Sung

“…The physical memory capacity of servers is expected to increase drastically with the deployment of the forthcoming non-volatile memory technologies. This is a…”
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