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

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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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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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.

“…Despite decades of improvement in compiler technology, it remains necessary to profile applications to improve performance. Existing profiling tools typically…”
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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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Guidelines for Assessing the Accuracy of Log Message Template Identification Techniques by Khan, Zanis Ali, Shin, Donghwan, Bianculli, Domenico, Briand, Lionel

“…Log message template identification aims to convert raw logs containing free-formed log messages into structured logs to be processed by automated log-based…”
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What Makes Good In-Context Demonstrations for Code Intelligence Tasks with LLMs? by Gao, Shuzheng, Wen, Xin-Cheng, Gao, Cuiyun, Wang, Wenxuan, Zhang, Hongyu, Lyu, Michael R.

“…Pre-trained models of source code have gained widespread popularity in many code intelligence tasks. Recently, with the scaling of the model and corpus size,…”
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An Empirical Study on Fine-Tuning Large Language Models of Code for Automated Program Repair by Huang, Kai, Meng, Xiangxin, Zhang, Jian, Liu, Yang, Wang, Wenjie, Li, Shuhao, Zhang, Yuqing

“…The advent of large language models (LLMs) has opened up new opportunities for automated program repair (APR). In particular, some recent studies have explored…”
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GPA: A GPU Performance Advisor Based on Instruction Sampling by Zhou, Keren, Meng, Xiaozhu, Sai, Ryuichi, Mellor-Crummey, John

“…Developing efficient GPU kernels can be difficult because of the complexity of GPU architectures and programming models. Existing performance tools only…”
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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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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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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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RobOT: Robustness-Oriented Testing for Deep Learning Systems by Wang, Jingyi, Chen, Jialuo, Sun, Youcheng, Ma, Xingjun, Wang, Dongxia, Sun, Jun, Cheng, Peng

“…Recently, there has been a significant growth of interest in applying software engineering techniques for the quality assurance of deep learning (DL) systems…”
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Performance Analysis with Bayesian Inference by Couderc, Noric, Reichenbach, Christoph, Soderberg, Emma

“…Statistics are part of any empirical science, and performance analysis is no exception. However, for non-statisticians, picking the right statistical tool to…”
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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

“…DNN popularity, which is driving advances in a growing number of fields, has increased the amount of computing resources running this kind of applications at…”
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White-Box Performance-Influence Models: A Profiling and Learning Approach (Replication Package) by Weber, Max, Apel, Sven, Siegmund, Norbert

“…These artifacts refer to the study and implementation of the paper 'White-Box Performance-Influence Models: A Profiling and Learning Approach'. In this…”
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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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Nuances are the Key: Unlocking ChatGPT to Find Failure-Inducing Tests with Differential Prompting by Li, Tsz-On, Zong, Wenxi, Wang, Yibo, Tian, Haoye, Wang, Ying, Cheung, Shing-Chi, Kramer, Jeff

“…Automated detection of software failures is an important but challenging software engineering task. It involves finding in a vast search space the…”
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Automatic Web Testing Using Curiosity-Driven Reinforcement Learning by Zheng, Yan, Liu, Yi, Xie, Xiaofei, Liu, Yepang, Ma, Lei, Hao, Jianye, Liu, Yang

“…Web testing has long been recognized as a notoriously difficult task. Even nowadays, web testing still mainly relies on manual efforts in many cases while…”
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Gamma: Revisiting Template-Based Automated Program Repair Via Mask Prediction by Zhang, Quanjun, Fang, Chunrong, Zhang, Tongke, Yu, Bowen, Sun, Weisong, Chen, Zhenyu

“…Automated program repair (APR) aims to fix software bugs without manual debugging efforts and plays a crucial role in software development and maintenance…”
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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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