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ISPASS 2023: Raleigh, NC, USA
- IEEE International Symposium on Performance Analysis of Systems and Software, ISPASS 2023, Raleigh, NC, USA, April 23-25, 2023. IEEE 2023, ISBN 979-8-3503-9739-0
- Geonhwa Jeong, Bikash Sharma, Nick Terrell, Abhishek Dhanotia, Zhiwei Zhao, Niket Agarwal, Arun Kejariwal, Tushar Krishna:
Characterization of Data Compression in Datacenters. 1-12 - Fatemeh Ghasemi, Lukas Liedtke
, Magnus Jahre:
PES: An Energy and Throughput Model for Energy Harvesting IoT Systems. 13-23 - Jiaao Ma, Ceyu Xu
PyTFHE: An End-to-End Compilation and Execution Framework for Fully Homomorphic Encryption Applications. 24-34 - Juan Gómez-Luna, Yuxin Guo, Sylvan Brocard, Julien Legriel, Remy Cimadomo, Geraldo F. Oliveira, Gagandeep Singh, Onur Mutlu:
Evaluating Machine LearningWorkloads on Memory-Centric Computing Systems. 35-49 - Shruti Yadav Narayana, Jie Tong, Anish Krishnakumar, Nuriye Yildirim, Emily Shriver, Mahesh Ketkar, Ümit Y. Ogras:
MQL: ML-Assisted Queuing Latency Analysis for Data Center Networks. 50-60 - Gino Chacon, Nathan Gober, Krishnendra Nathella, Paul V. Gratz, Daniel A. Jiménez:
A Characterization of the Effects of Software Instruction Prefetching on an Aggressive Front-end. 61-70 - Emilio Domínguez-Sánchez, Alberto Ros:
MBPlib: Modular Branch Prediction Library. 71-80 - John Alistair Kressel, Guillermo Callaghan, Cosmin Gorgovan, Mikel Luján:
Evaluating the Impact of Optimizations for Dynamic Binary Modification on 64-bit RISC-V. 81-91 - Anna Yue, Sanyam Mehta:
An Application-Oriented Approach to Designing Hybrid CPU Architectures. 92-102 - Johnson Umeike
Profiling gem5 Simulator. 103-113 - Markos Kynigos, Javier Navaridas, Jose Antonio Pascual, Mikel Luján:
A Novel Simulation Methodology for Silicon Photonic Switching Fabrics. 114-123 - Stijn Eyerman, Sam Van den Steen, Wim Heirman, Ibrahim Hur:
Simulating Wrong-Path Instructions in Decoupled Functional-First Simulation. 124-133 - Alexander Hankin, Lillian Pentecost, Dongmoon Min, David Brooks, Gu-Yeon Wei:
Is the Future Cold or Tall? Design Space Exploration of Cryogenic and 3D Embedded Cache Memory. 134-144 - Mohsin Shan, Deniz Gurevin, Jared Nye, Caiwen Ding, Omer Khan:
MergePath-SpMM: Parallel Sparse Matrix-Matrix Algorithm for Graph Neural Network Acceleration. 145-156 - Shvetank Prakash, Tim Callahan, Joseph Bushagour, Colby R. Banbury, Alan V. Green, Pete Warden, Tim Ansell, Vijay Janapa Reddi:
CFU Playground: Full-Stack Open-Source Framework for Tiny Machine Learning (TinyML) Acceleration on FPGAs. 157-167 - Matthew Joseph Adiletta, Jesmin Jahan Tithi, Emmanouil-Ioannis Farsarakis
Characterizing the Scalability of Graph Convolutional Networks on Intel® PIUMA. 168-177 - Zhuren Liu, Shouzhe Zhang, Justin Garrigus, Hui Zhao:
Genomics-GPU: A Benchmark Suite for GPU-accelerated Genome Analysis. 178-188 - Lauren Biernacki, Biniyam Mengist Tiruye, Meron Zerihun Demissie, Fitsum Assamnew Andargie
Exploring the Efficiency of Data-Oblivious Programs. 189-200 - Yanwen Xu, Ang Li
Redwood: Flexible and Portable Heterogeneous Tree Traversal Workloads. 201-213 - Vignesh Balaji
Community-based Matrix Reordering for Sparse Linear Algebra Optimization. 214-223 - Mahmood Naderan-Tahan, Hossein SeyyedAghaei, Lieven Eeckhout:
Sieve: Stratified GPU-Compute Workload Sampling. 224-234 - Maurus Item, Geraldo F. Oliveira, Juan Gómez-Luna, Mohammad Sadrosadati, Yuxin Guo, Onur Mutlu:
TransPimLib: Efficient Transcendental Functions for Processing-in-Memory Systems. 235-247 - Seokjin Go
Early-Adaptor: An Adaptive Framework forProactive UVM Memory Management. 248-258 - MohammadHossein Olyaiy, Christopher Ng, Alexandra (Sasha) Fedorova, Mieszko Lis:
Sunstone: A Scalable and Versatile Scheduler for Mapping Tensor Algebra on Spatial Accelerators. 259-271 - Deepraj Soni, Negar Neda, Naifeng Zhang
RPU: The Ring Processing Unit. 272-282 - William Won
ASTRA-sim2.0: Modeling Hierarchical Networks and Disaggregated Systems for Large-model Training at Scale. 283-294 - Maziar Amiraski, David Werner, Alexander Hankin, Julien Sebot, Kaushik Vaidyanathan, Mark Hempstead
Boreas: A Cost-Effective Mitigation Method for Advanced Hotspots using Machine Learning and Hardware Telemetry. 295-305 - Diksha Moolchandani
AMPeD: An Analytical Model for Performance in Distributed Training of Transformers. 306-315 - Michael Gilbert, Yannan Nellie Wu, Angshuman Parashar, Vivienne Sze, Joel S. Emer:
LoopTree: Enabling Exploration of Fused-layer Dataflow Accelerators. 316-318 - Sanya Srivastava, Tyler Sorensen:
Degree-Aware Kernel Mapping for Graph Processing on GPUs. 319-321 - Mahita Nagabhiru
lfbench: a lock-free microbenchmark suite. 322-324 - Zheming Jin, Jeffrey S. Vetter:
A Benchmark Suite for Improving Performance Portability of the SYCL Programming Model. 325-327 - Tom Glint, Aryan Gupta, Daniel Giftson, Gaurav Shah, Vrajesh Patel, Ruchit Chudasama, Sukanya More, Joycee Mekie:
Impact of Optimal Design Point on Performance Metrics of DNN accelerators in FPGA. 328-330 - Lina Sawalha, Grant Deljevic:
Workload Characterization Using Hierarchical PCA. 331-333 - Jinghan Huang, Jiaqi Lou, Yan Sun, Tianchen Wang, Eun Kyung Lee, Nam Sung Kim:
Analyzing Energy Efficiency of a Server with a SmartNIC under SLO Constraints. 334-336 - Athanasios Kordelas, Thanasis Spyrou, Spyros Voulgaris, Vasileios Megalooikonomou, Nikos Deligiannis:
KORDI: A Framework for Real-Time Performance and Cost Optimization of Apache Spark Streaming. 337-339 - Maryam Babaie, Ayaz Akram, Jason Lowe-Power:
Enabling Design Space Exploration of DRAM Caches for Emerging Memory Systems. 340-342 - Ying Li, Yifan Sun, Adwait Jog:
A Regression-based Model for End-to-End Latency Prediction for DNN Execution on GPUs. 343-345 - Massimo Coluzzi, Amos Brocco, Patrizio Contu, Tiziano Leidi
A survey and comparison of consistent hashing algorithms. 346-348 - Tom Glint, Chandan Kumar Jha, Manu Awasthi, Joycee Mekie:
Analysis of Conventional, Near-Memory, and In-Memory DNN Accelerators. 349-351 - Stavroula Zouzoula, Muhammad Waqar Azhar, Pedro Trancoso:
RAINBOW: Multi-Dimensional Hardware-Software Co-Design for DL Accelerator On-Chip Memory. 352-354 - Arne Symons
Stream: A Modeling Framework for Fine-grained Layer Fusion on Multi-core DNN Accelerators. 355-357
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