| 时间 | 主讲人 | 论文题目 | 附件 | 会议/期刊 |
| 2024.01.10 | 软工组，王西霖 | Characterizing a Memory Allocator at Warehouse Scale BEVGPT: Generative Pre-trained Foundation Model for Autonomous Driving Prediction, Decision-Making, and Planning |  软工组.pptx2025-01-10-zhou2024characterizingmemoryallocator.pptx BEVGPT_Generative_Pre-trained_Foundation_Model_for_Autonomous_Driving_Prediction_Decision-Making_and_Planning.pdfBEVGPT论文精度报告.pdf | ASPLOS 2024 TIV 2024 |
| 2024.01.03 | 图数据组，刘烁 | Aligning Large Language Models to a Domain-specific Graph Database for NL2GQL D-Bot: Database Diagnosis System using Large Language Models PixelSieve: Towards Efficient Activity Analysis From Compressed Video Streams | Aligning Large Language Models to a Domain-specific Graph Database for NL2GQL.pdfD-Bot_VLDB2024.pdfPixelSieve_Towards_Efficient_Activity_Analysis_From_Compressed_Video_Streams.pdfPixelSieve阅读组会精读报告.pdf | CIKM 202 4 arXiv 2023 DAC 2021 |
| 2024.12.27 | 王贺 | FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning | Dao - Faster Attention with Better Parallelism and Work Partitioning.pdfDao 等 - 2022 - FlashAttention Fast and Memory-Efficient Exact Attention with IO-Awareness.pdf | ICLR 2024 |
| 2024.12.20 | 杨哲骏，唐富根 | LLM-Generated Invariants for Bounded Model Checking Without Loop Unrolling Lost in Translation: A Study of Bugs Introduced by Large Language Models while Translating Code | 组会精读_LLM_for_BMC.pptxLost in Translation A Study of Bugs Introduced by Large Language Models while Translating Code - 2024.pdf | ASE 2024 arXiv 2024 |
2024.12.13 | 向红静 | Scenic: A Language for Scenario Specification and Scene Generation | Scenic A Language for Scenario Specification and.pdfscenic2019精度笔记.pdf | PLDI 2019 |
| 2024.1206 | 郑钊雨 | Qbit Recycling Revisited | Qubit Recycling Revisited.pdfQubit_Recycling_Revisited阅读笔记.pdf | PL 2024 |
| 2024.11.29 | 栗花伟，孙新雨 | Design and Implementation of RTE Generator for Automotive Embedded Software CYCLE: Learning to Self-Refine the Code Generation | Design_and_Inmplementation_of_RTE_Generator_for_Automotive_Embedded_Software.pdfCYCLE Learning to Self-Refine the Code Generation.pdf | SERA 2009 OOPSLA 2024 |
| 2024.11.22 | 徐柴俊 | Implementation Strategies for Views over Property Graphs | sigmod2024-ImplementationStrategiesforViewsOverPropertyGraphs.pptx精读报告_sigmod2024-ImplementationStrategiesforViewsOverPropertyGraphs.pdf | SIGMOD 2024 |
| 2024.11.15 | 石磊鑫 | Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation | DAIL-SQL.pptx阅读报告DAIL-SQL.pdf | arXiv 2023 |
| 2024.11.08 | 邓皓苧 | Noisy random quantum circuits and its classical simulation | dhn-20241108-阅读组会.pptxdhn20241108精读报告.pdf | QUTE |
| 2024.11.01 | 丁伯尧 | Reusable Inline Caching for JavaScript Performance | Resuable IC for JS.pptxReusable Inline Caching for JavaScript Performance.pdf | PLDI 2019 |
| 2024.10.25 | 刘硕 | TSCompiler: efficient compilation framework for dynamic-shape models | TSCompiler.pptx TSCompiler.docx | SCIS 2024 |
| 2024.10.18 | 孙策 | PowerInfer-2: Fast Large Language Model Inference on a Smartphone | PowerInfer 2 精读报告.docxpowerinfer2.pptx | arXiv 2024 |
| 2024.10.11 | 陈金宝 | Fine-tuning Large Language Models to Improve Accuracy and Comprehensibility of Automated Code Review | TOSEM24LLM4CodeReview.pptx20241011阅读组会精读报告.docx | TOSEM 2024 |
| 2024.09.27 | 李清伟 | An Empirical Study on the Effectiveness of Static C Code Analyzers for Vulnerability Detection | 2024-09-27阅读组会精读报告.docxlipp2022effectivenessStaticCAnalyzer.pptx | ISSTA 2022 |
| 2024.09.20 | 陈铭瑜 | Quanto: optimizing quantum circuits with automatic generation of circuit identities | 202409-Quanto.pptx | QST 2024 |
| 2024.09.13 | 赖民信 | Heimdall: mobile GPU coordination platform for augmented reality applications | Heimdall_阅读报告.pdf阅读组会240913-Heimdall.pptx | MobiCom 2020 |
| 2024.09.06 | 李永尚 | A digital-analog quantum genetic algorithm using Rydberg atom arrays | DAQC.pptxDAQC笔记.docx | arXiv 2024 |
| 2024.07.09 | 丁伯尧、栗花伟 | 论文一：JavaScript Performance Tuning as a Crowdsourced Service 论文二：Prioritizing Testing Instances to Enhance the Robustness of Object Detection Systems | DeepView.pptxTMC2023 JS Performance Tuning.pptx | TMC 2023 Internetware 2023 |
| 2024.7.2 | 赖民信 | 智能无人系统小组汇报 | 阅读组会240702-智能无人系统小组.pptx | |
| 2024.6.25 | 李永尚 | 量子组专题报告 | 量子组专题报告.pptx | |
| 2024.6.18 | 万嘉诚 | ASPEN: Breaking Operator Barriers for Efficient Parallel Execution of Deep Neural Networks | ASPEN.pptx | NIPS 2023 |
| 2024.5.21 | 孙策 梁运龙 | Chimera: An Analytical Optimizing Framework for Effective Compute-intensive Operators Fusion DBSP: Automatic Incremental View Maintenance for Rich Query Languages | chimera.pptx精读报告-chimera.pdfvldb2023-精读.pptx | HPCA 2023 VLDB 2023 |
| 2024.5.14 | 徐柴俊 | Reducing Property Graph Queries to Relational Algebra for Incremental View Maintenance | Reducing Property Graph Queries to Relational Algebra for Incremental View Maintenance.pptxReducing Property Graph Queries to Relational Algebra for Incremental View Maintenance_笔记.pdf | SIGMOD'18 |
| 2024.5.7 | 谭泽霖 | SARATHI: Efficient LLM Inference by Piggybacking Decodes with Chunked Prefills | SARATHI.pdf | |
| 2024.4.30 | 刘硕、季扬、孙新雨、谭泽霖 | 计算优化组专题报告 | ICDE2020_Kaskade_Graph_Views_for_Efficient_Graph_Analytics.pptx计算优化组阅读组会-v2.pptx | |
| 2024.4.23 | 黄庄湫 | TOKEN MERGING: YOUR VIT BUT FASTER | ICLR2023_ToMe笔记.pdfICDE2020_Kaskade_Graph_Views_for_Efficient_Graph_Analytics.pptx | ICLR 2023 |
| 2024.4.16 | 龚磊 | 数据组专题报告 | 数据组阅读组会(3).pptx | |
| 2024.4.9 | 刘硕 | Optimizing Dynamic-Shape Neural Networks on Accelerators via On-the-Fly Micro-Kernel | MikPoly-ASPLOS24.pptx | ASPLOS 2024 |
| 2024.4.2 | 丁伯尧 陈金宝 李清伟 唐富根 石磊鑫 | 程序分析组专题报告 | LLM漏洞检测.pptx | |
| 2024.3.26 | 胡海蓉、李清伟 | Reason2Drive: Towards Interpretable and Chain-based Reasoning for Autonomous Driving Enhancing Static Analysis for Practical Bug Detection: An LLM-Integrated Approach | Reason2Drive.pdf2024-3-26-SPA-LLM.pdfslides-li2024llmenhancingstaticanalysis-handout.pdf | OOPSLA'24 |
| 2024.3.19 | 龚磊 | A ConvNet for the 2020s （ConvNext） | ConvNext.pptx | CVPR 2020 |
| 2024.3.5 | 陈金宝 | Less is More? An Empirical Study on Configuration Issues in Python PyPI Ecosystem | ICSE24PyConf.pptx | ICSE 2024 |
| 2024.2.27 | 李永尚 | Mapping of lattice surgery-based quantum circuits on surface code architectures | QST2019.pptxQST2019笔记.docx | QST 2019 |
| 2024.1.30 | 万嘉诚 | Performance modeling on DaVinci AI core | 季扬-精读.pptx季扬-精读报告.pdf | MICRO 2023 |
| 2024.1.30 | 丁伯尧 | Precise and Scalable Points-to Analysis via Data-Driven Context Tunneling | OOPSLA2018 Precise and Scalable Points-to Analysis via Data-Driven.pptxPrecise and Scalable Points-to Analysis via Data-Driven Context Tunneling.pdf | OOPLAS 2018 |
| 2024.1.30 | 万嘉诚 | AGO: Boosting Mobile AI Inference Performance by Removing Constraints on Graph Optimization | AGO汇报.pptxAGO精度报告.pdf | INFOCOM 2023 |
| 2024.1.23 | 杨天峰 | BladeDISC: Optimizing Dynamic Shape Machine Learning Workloads via Compiler Approach | BladeDISC.pptx精读报告.docx | PACM 2023 |
| 2024.1.23 | 王天宸 | FLAT: An Optimized Dataflow forMitigating Attention Bottlenecks | FLAT__An_Optimized_Dataflow_forMitigating_Attention_Bottlenecks.pptx王天宸 精读报告.pdf | ASPLOS 2023 |
| 2024.1.9 | 邓皓苧 | QuCT: A Framework for Analyzing Quantum Circuit by Extracting Contextual and Topological Features | 阅读组会分享.pptx邓皓苧精读报告.pdf | MICRO 2023 |
| 2024.1.2 | 唐富根 | Who goes first? detecting go concurrency bugs via message reordering | GFUZZ.pptx唐富根精读报告.pdf | ASPLOS 2022 |
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