Heterogeneous Systems Seminar

Papers:

Nonvolatile Memory

• Moinuddin K. Qureshi, Vijayalakshmi Srinivasan, and Jude A. Rivers. "Scalable High Performance Main Memory System Using Phase-Change Memory Technology". In: SIGARCH Comput. Archit. News 37.3 (June 2009) url: external pagehttps://doi.org/10.1145/1555815.1555760call_made
  Joy Arulraj and Andrew Pavlo. "How to Build a Non-Volatile Memory Database Management System". In: Proceedings of the 2017 ACM International Conference on Management of Data. SIGMOD '17. Chicago, Illinois, USA: Association for Computing Machinery, 2017, url: external pagehttps://doi.org/10.1145/3035918.3054780call_made
  
• Assaf Eisenman et al. "Reducing DRAM Footprint with NVM in Facebook". In: Proceedings of the Thirteenth EuroSys Conference. EuroSys '18. Porto, Portugal: Association for Computing Machinery, 2018. url: external pagehttps://doi.org/10.1145/3190508.3190524call_made
  Amanda Raybuck et al. "HeMem: Scalable Tiered Memory Management for Big Data Applications and Real NVM". In: Proceedings of the ACM SIGOPS 28th Symposium on Operating Systems Principles. SOSP '21. Virtual Event, Germany: Association for Computing Machinery, 2021, url: external pagehttps://doi.org/10.1145/3477132.3483550call_made
• Wang et al, "SEPH: Scalable, Efficient, and Predictable Hashing on Persistent Memory" OSDI'23, url: external pagehttps://www.usenix.org/conference/osdi23/presentation/wang-chaocall_made

Disaggregated Memory

• Huaicheng Li, et al. "Pond: CXL-Based Memory Pooling Systems for Cloud Platforms". In Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2 (ASPLOS 2023). Association for Computing Machinery, New York, NY, USA, 574–587. external pagehttps://doi.org/10.1145/3575693.3578835call_made
  Zhiyuan Guo et al. "Clio: a hardware-software co-designed disaggregated memory system". In Proceedings of the 27th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS '22). Association for Computing Machinery, New York, NY, USA, 417–433. external pagehttps://doi.org/10.1145/3503222.3507762call_made
• Hasan Al Maruf, et al. "TPP: Transparent Page Placement for CXL-Enabled Tiered-Memory". In Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 3 (ASPLOS 2023). Association for Computing Machinery, New York, NY, USA, 742–755. external pagehttps://doi.org/10.1145/3582016.3582063call_made
  In-Memory Processing/Near-memory processing
• Pati et al. "T3: Transparent Tracking & Triggering for Fine-grained Overlap of Compute & Collectives" to appear in ASPLOS 2024 external pagehttps://arxiv.org/abs/2401.16677call_made

GPUs:

• John Nickolls et al. "Scalable Parallel Programming with CUDA: Is CUDA the Parallel Programming Model That Application Developers Have Been Waiting For?" In: Queue 6.2 (Mar. 2008), pp. 40{53. issn: 1542-7730. doi: 10.1145/1365490.1365500. url: external pagehttps://doi.org/10.1145/1365490.1365500call_made
• Victor W. Lee et al. "Debunking the 100X GPU vs. CPU Myth: An Evaluation of Throughput Computing on CPU and GPU". In: Proceedings of the 37th Annual International Symposium on Computer Architecture. ISCA '10. Saint-Malo, France: Association for Computing Machinery, 2010, url: external pagehttps://doi.org/10.1145/1815961.1816021call_made
  
• Lin Shi et al. "vCUDA: GPU-Accelerated High-Performance Computing in Virtual Machines". In: IEEE Transactions on Computers 61.6 (2012), url: external pagehttps://ieeexplore.ieee.org/document/5928326call_made
  
• Anil Shanbhag, Samuel Madden, and Xiangyao Yu. "A Study of the Fundamental Performance Characteristics of GPUs and CPUs for Database Analytics". In: Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data. SIGMOD '20. Portland, OR, USA: Association for Computing Machinery, 2020 url: external pagehttps://doi.org/10.1145/3318464.3380595call_made
  

FPGAs:

• Adrian M. Caul eld et al. "A cloud-scale acceleration architecture". In: 2016 49th Annual IEEE/ACM International Symposium on Microarchitecture (MICRO). 2016 external pagehttps://www.doi.org/10.1109/MICRO.2016.7783710call_made
  
• David Sidler et al. "DoppioDB: A Hardware Accelerated Database". In: Proceedings of the 2017 ACM International Conference on Management of Data. SIGMOD '17. Chicago, Illinois, USA: Association for Computing Machinery, 2017, url: external pagehttps://doi.org/10.1145/3035918.3058746call_made
• Young-Kyu Choi et al. "In-Depth Analysis on Microarchitectures of Modern Heterogeneous CPU-FPGA Platforms". In: ACM Trans. Recon gurable Technol. Syst. 12.1 (Feb. 2019). url: external pagehttps://doi.org/10.1145/3294054call_made
  
• Jiacheng Ma et al. "A Hypervisor for Shared-Memory FPGA Platforms". In: Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems. New York, NY, USA: Association for Computing Machinery, 2020, url: external pagehttps://doi.org/10.1145/3373376.3378482call_made
  
  

Analog Computing:

• G.E.R. Cowan, R.C. Melville, and Y.P. Tsividis. "A VLSI analog computer/digital computer accelerator". In: IEEE Journal of Solid-State Circuits 41.1 (2006), pp. 42-53. external pagehttps://www.doi.org/10.1109/JSSC.2005.858618call_made
  
• Suma George et al. "A Programmable and Con gurable Mixed-Mode FPAA SoC". In: IEEE Transactions on Very Large Scale Integration (VLSI) Systems 24.6 (2016), doi: external pagehttps://www.doi.org/10.1109/TVLSI.2015.2504119call_made
  
• Wilfried Haensch, Tayfun Gokmen, and Ruchir Puri. "The Next Generation of Deep Learning Hardware: Analog Computing". In: Proceedings of the IEEE 107.1 (2019), doi: external pagehttps://www.doi.org/10.1109/JPROC.2018.2871057call_made

In-Network Computing:

• Firestone, Daniel, et al. "Azure accelerated networking: Smartnics in the public cloud." 15th USENIX Symposium on Networked Systems Design and Implementation (NSDI 18). 2018. external pagehttps://www.usenix.org/conference/nsdi18/presentation/firestonecall_made
  
• Jongyul Kim, et al. LineFS: Efficient SmartNIC Offload of a Distributed File System with Pipeline Parallelism. In Proceedings of the ACM SIGOPS 28th Symposium on Operating Systems Principles (SOSP '21). external pagehttps://doi.org/10.1145/3477132.3483565call_made
  
• Lao, ChonLam, et al. "ATP: In-network Aggregation for Multi-tenant Learning." NSDI. Vol. 21. 2021. external pagehttps://www.usenix.org/conference/nsdi21/presentation/laocall_made
  
• Yongchao He, et al, "A Generic Service to Provide In-Network Aggregation for Key-Value Streams". In Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2 (ASPLOS 2023). Association for Computing Machinery, New York, NY, USA, 33–47. external pagehttps://doi.org/10.1145/3575693.3575708call_made
  
  

Custom Accelerators:

• Song Han et al. "EIE: Effcient Inference Engine on Compressed Deep Neural Network". In: 2016 ACM/IEEE 43rd Annual International Symposium on Computer Architecture (ISCA). 2016, pp. 243-254. doi: https://ieeexplore.ieee.org/document/7551397
  
• Norman P. Jouppi et al. "In-Datacenter Performance Analysis of a Tensor Processing Unit". In: SIGARCH Comput. Archit. News 45.2 (June 2017), url: https://doi.org/10.1145/3140659.3080246
  
• Norm Jouppi, et al. "TPU v4: An Optically Reconfigurable Supercomputer for Machine Learning with Hardware Support for Embeddings". In Proceedings of the 50th Annual International Symposium on Computer Architecture (ISCA '23). Association for Computing Machinery, New York, NY, USA, Article 82, 1–14. external pagehttps://doi.org/10.1145/3579371.3589350call_made
  
• Yatish Turakhia, Gill Bejerano, and William J. Dally. "Darwin: A Genomics Co-Processor Provides up to 15,000X Acceleration on Long Read Assembly". In: SIGPLAN Not. 53.2 (Mar. 2018), url: external pagehttps://doi.org/10.1145/3296957.3173193call_made
  
• Parthasarathy Ranganathan et al. \Warehouse-Scale Video Acceleration: Co-Design and Deployment in the Wild". In: Proceedings of the 26th ACM International Conference on Architectural Support for Programming Languages and Operating Systems. ASPLOS 2021. Virtual, USA: Association for Computing Machinery, 2021, url: external pagehttps://doi.org/10.1145/3445814.3446723call_made
  
• Yakun Sophia Shao, et al. "Simba: Scaling Deep-Learning Inference with Multi-Chip-Module-Based Architecture". In Proceedings of the 52nd Annual IEEE/ACM International Symposium on Microarchitecture (MICRO '52). Association for Computing Machinery, New York, NY, USA, 14–27. external pagehttps://doi.org/10.1145/3352460.3358302call_made

Wild Card

• Zaruba, Florian, Fabian Schuiki, and Luca Benini. "Manticore: A 4096-core RISC-V chiplet architecture for ultraefficient floating-point computing." IEEE Micro 41.2 (2020) url: external pagehttps://ieeexplore.ieee.org/abstract/document/9296802call_made
  external pagecall_made
• Jennifer Switzer, et. "Junkyard Computing: Repurposing Discarded Smartphones to Minimize Carbon". In Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems, Volume 2 (ASPLOS 2023). Association for Computing Machinery, New York, NY, USA, 400–412. external pagehttps://doi.org/10.1145/3575693.3575710call_made