Search Results - General and reference Cross-computing tools and techniques*

OptiWISE: Combining Sampling and Instrumentation for Granular CPI Analysis by Guo, Yuxin, Chadwick, Alex W., Erdos, Marton, Bora, Utpal, Vougioukas, Ilias, Gabrielli, Giacomo, Jones, Timothy M.

“… Existing profiling tools typically either sample hardware performance counters or instrument the program with extra instructions to analyze its execution…”
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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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GPA: A GPU Performance Advisor Based on Instruction Sampling by Zhou, Keren, Meng, Xiaozhu, Sai, Ryuichi, Mellor-Crummey, John

“… Existing performance tools only provide coarse-grained tuning advice at the kernel level…”
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Revamping Sampling-Based PGO with Context-Sensitivity and Pseudo-instrumentation by He, Wenlei, Yu, Hongtao, Wang, Lei, Oh, Taewook

“…The ever increasing scale of modern data center demands more effective optimizations, as even a small percentage of performance improvement can result in a…”
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Performance Analysis with Bayesian Inference by Couderc, Noric, Reichenbach, Christoph, Soderberg, Emma

“… However, for non-statisticians, picking the right statistical tool to answer a research question can be challenging…”
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Performance Characterization of Popular DNN Models on Out-of-Order CPUs by Prieto, Pablo, Abad, Pablo, Gregorio, Jose Angel, Puente, Valentin

“… However, the ubiquity of DNN models is rapidly extending the presence of this software to general-purpose CPUs…”
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White-Box Performance-Influence Models: A Profiling and Learning Approach (Replication Package) by Weber, Max, Apel, Sven, Siegmund, Norbert

“… Specifically, we describe the general steps and tools that we have used to implement our approach, the data we have obtained, and the evaluation setup…”
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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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The Architecture value engine: Measuring and delivering sustainable SoC improvement by Carballo, Juan-Antonio, Bangqi Xu

“…The value of semiconductor-based systems continues to increase rapidly especially when considering the cost associated with building it. As such, Moore's Law…”
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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…”
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Probing for Requirements Knowledge to Stimulate Architectural Thinking by Anish, Preethu Rose, Balasubramaniam, Balaji, Sainani, Abhishek, Cleland-Huang, Jane, Daneva, Maya, Wieringa, Roel J., Ghaisas, Smita

“…Software requirements specifications (SRSs) often lack the detail needed to make informed architectural decisions. Architects therefore either make…”
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Exploiting Input Sanitization for Regex Denial of Service by Barlas, Efe, Du, Xin, Davis, James C.

“…Web services use server-side input sanitization to guard against harmful input. Some web services publish their sanitization logic to make their client…”
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White-Box Performance-Influence Models: A Profiling and Learning Approach by Weber, Max, Apel, Sven, Siegmund, Norbert

“…Many modern software systems are highly configurable, allowing the user to tune them for performance and more. Current performance modeling approaches aim at…”
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Top-Down Microarchitecture Analysis Approximation Based on Performance Counter Architecture for SiFive RISC-V Processors by Mou, Chan-Yu, Hsiao, Chao-Chieh, Chou, Jerry

“…Modern Out-of-Order RISC-V CPUs have complex mechanisms, making microarchitecture-level performance analysis challenging. Despite increasing Performance…”
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Analyzing and Improving Resilience and Robustness of Autonomous Systems (Invited Paper) by Wan, Zishen, Swaminathan, Karthik, Chen, Pin-Yu, Chandramoorthy, Nandhini, Raychowdhury, Arijit

“…Autonomous systems have reached a tipping point, with a myriad of self-driving cars, unmanned aerial vehicles (UAVs), and robots being widely applied and…”
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MemSeer: Leverage Memory Failure Distinctions and Multi-Grained Prediction in Ultra-Scale Heterogeneous X86/ARM Clusters by Gu, Yunfei, Liu, Yixuan, Wu, Xinyuan, Shao, Bo, Wu, Chentao, Li, Shiyi, Zhao, Jieru, Li, Jie, Guo, Minyi, Yang, Kunlin, Zhang, Wengui, Lin, Feilong

“… We introduce MemSeer, an AIOps-integrated tool that utilizes a multi-grained memory failure prediction approach for x86/ARM heterogeneous clusters…”
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Multi-level Memory-Centric Profiling on ARM Processors with ARM SPE by Miksits, Samuel, Shi, Ruimin, Gokhale, Maya, Wahlgren, Jacob, Schieffer, Gabin, Peng, Ivy

“… Many existing memory profiling tools leverage hardware performance counters and precise event sampling, such as Intel PEBS and AMD IBS, to achieve high accuracy and low overhead…”
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Ponte Vecchio Across the Atlantic: Single-Node Benchmarking of Two Intel GPU Systems by Applencourt, Thomas, Sadawarte, Aditya, Muralidharan, Servesh, Bertoni, Colleen, Kwack, JaeHyuk, Luo, Ye, Rangel, Esteban, Tramm, John, Ghadar, Yasaman, Tamerus, Arjen, Edsall, Chris, Deakin, Tom

“…Intel Data Center GPU Max 1550, known as Ponte Vecchio (PVC), is a new Intel GPU architecture for high-performance computing. It is the basis of two systems on…”
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PracMHBench: Re-evaluating Model-Heterogeneous Federated Learning Based on Practical Edge Device Constraints by Guo, Yuanchun, Liu, Bingyan, Sha, Yulong, Xian, Zhensheng

“…Federating heterogeneous models on edge devices with diverse resource constraints has been a notable trend in recent years. Compared to traditional federated…”
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Scaler: Efficient and Effective Cross Flow Analysis by Tang, Jiaxun, Xiang, Mingcan, Wang, Yang, Wu, Bo, Chen, Jianjun, Liu, Tongping

“…) of a complex system can interact with each other. However, few existing tools focus on understanding such interactions…”
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