| 60 |
Efficiently Compiling Efficient Query Plans for Modern Hardware |
2011 |
VLDB |
0.00064439773 |
| 115 |
Eddies: Continuously Adaptive Query Processing |
2000 |
SIGMOD |
0.00046221215 |
| 411 |
PyTorch Distributed: Experiences on Accelerating Data Parallel Training |
2020 |
VLDB |
0.00023906921 |
| 650 |
Robust Query Processing through Progressive Optimization |
2004 |
SIGMOD |
0.00018659177 |
| 1,402 |
Hybrid Parallelization Strategies for Large-Scale Machine Learning in SystemML |
2014 |
VLDB |
0.00012180605 |
| 1,873 |
An Architecture for Compiling UDF-centric Workflows |
2015 |
VLDB |
0.00010253002 |
| 1,882 |
Tuplex: Data Science in Python at Native Code Speed |
2021 |
SIGMOD |
0.0001021625 |
| 2,067 |
HippogriffDB: Balancing I/O and GPU Bandwidth in Big Data Analytics |
2016 |
VLDB |
9.6392739e-05 |
| 2,121 |
Balsa: Learning a Query Optimizer Without Expert Demonstrations |
2022 |
SIGMOD |
9.5017232e-05 |
| 2,287 |
Pipelined Query Processing in Coprocessor Environments |
2018 |
SIGMOD |
9.0972606e-05 |
| 2,688 |
Accelerating Recommendation System Training by Leveraging Popular Choices |
2022 |
VLDB |
8.2991144e-05 |
| 2,896 |
Evaluating End-to-End Optimization for Data Analytics Applications in Weld |
2018 |
VLDB |
7.9452051e-05 |
| 3,025 |
NeutronStar: Distributed GNN Training with Hybrid Dependency Management |
2022 |
SIGMOD |
7.6906935e-05 |
| 3,918 |
On Optimizing Operator Fusion Plans for Large-Scale Machine Learning in SystemML |
2018 |
VLDB |
6.6315176e-05 |
| 4,802 |
Resource Elasticity for Large-Scale Machine Learning |
2015 |
SIGMOD |
5.9114415e-05 |
| 4,948 |
Designing an Open Framework for Query Optimization and Compilation |
2022 |
VLDB |
5.8116879e-05 |
| 5,052 |
HET-GMP: A Graph-based System Approach to Scaling Large Embedding Model Training |
2022 |
SIGMOD |
5.7337977e-05 |
| 5,088 |
TCUDB: Accelerating Database with Tensor Processors |
2022 |
SIGMOD |
5.7072189e-05 |
| 5,333 |
Heterogeneity-Aware Distributed Machine Learning Training via Partial Reduce |
2021 |
SIGMOD |
5.5656575e-05 |
| 5,988 |
NuPS: A Parameter Server for Machine Learning with Non-Uniform Parameter Access |
2022 |
SIGMOD |
5.2430981e-05 |
| 6,369 |
Improving Execution Efficiency of Just-in-time Compilation based Query Processing on GPUs |
2021 |
VLDB |
5.0936663e-05 |
| 6,377 |
Galvatron: Efficient Transformer Training over Multiple GPUs Using Automatic Parallelism |
2023 |
VLDB |
5.0911095e-05 |
| 6,648 |
Grizzly: Efficient Stream Processing Through Adaptive Query Compilation |
2020 |
SIGMOD |
4.9771723e-05 |
| 7,823 |
Measuring and Optimizing Distributed Array Programs |
2016 |
VLDB |
4.6419393e-05 |
| 8,262 |
FuseME: Distributed Matrix Computation Engine based on Cuboid-based Fused Operator and Plan Generation |
2022 |
SIGMOD |
4.5467867e-05 |
| 8,479 |
Excalibur: A Virtual Machine for Adaptive Fine-grained JIT-Compiled Query Execution based on VOILA |
2023 |
VLDB |
4.5014929e-05 |
| 8,607 |
Harmony: Overcoming the Hurdles of GPU Memory Capacity to Train Massive DNN Models on Commodity Servers |
2022 |
VLDB |
4.4855009e-05 |
| 8,982 |
Optimizing Inference Serving on Serverless Platforms |
2022 |
VLDB |
4.4166105e-05 |
| 9,265 |
COMET: A Novel Memory-Efficient Deep Learning Training Framework by Using Error-Bounded Lossy Compression |
2022 |
VLDB |
4.3667558e-05 |
| 9,705 |
ETO: Accelerating Optimization of DNN Operators by High-Performance Tensor Program Reuse |
2022 |
VLDB |
4.2994163e-05 |