Brief Industry Paper: Enabling Level-4 Autonomous Driving on a Single $1k Off-the-Shelf Card | 1 | 0.34 | 2022 |
Bit-GraphBLAS: Bit-Level Optimizations of Matrix-Centric Graph Processing on GPU | 0 | 0.34 | 2022 |
Temporal Exposure Reduction Protection for Persistent Memory | 0 | 0.34 | 2022 |
Exploring Data Analytics Without Decompression on Embedded GPU Systems | 2 | 0.37 | 2022 |
Energy Efficient Boosting of GEMM Accelerators for DNN via Reuse | 0 | 0.34 | 2022 |
Sequential Model Optimization for Software Effort Estimation | 0 | 0.34 | 2022 |
FFCCD: fence-free crash-consistent concurrent defragmentation for persistent memory | 0 | 0.34 | 2022 |
Preserving Addressability Upon GC-Triggered Data Movements on Non-Volatile Memory | 0 | 0.34 | 2022 |
GCD<sup>2</sup>: A Globally Optimizing Compiler for Mapping DNNs to Mobile DSPs | 0 | 0.34 | 2022 |
Enabling Near Real-Time NLU-Driven Natural Language Programming through Dynamic Grammar Graph-Based Translation | 0 | 0.34 | 2022 |
General Reuse-Centric CNN Accelerator | 0 | 0.34 | 2022 |
Reuse-centric k-means configuration | 0 | 0.34 | 2021 |
How to “DODGE” Complex Software Analytics | 4 | 0.36 | 2021 |
Brief Industry Paper: Towards Real-Time 3D Object Detection for Autonomous Vehicles with Pruning Search | 0 | 0.34 | 2021 |
Exploring deep reuse in winograd CNN inference | 1 | 0.35 | 2021 |
Revisit the Scalability of Deep Auto-Regressive Models for Graph Generation | 0 | 0.34 | 2021 |
G-Tadoc: Enabling Efficient Gpu-Based Text Analytics Without Decompression | 1 | 0.35 | 2021 |
Rt3d: Achieving Real-Time Execution Of 3d Convolutional Neural Networks On Mobile Devices | 0 | 0.34 | 2021 |
HPCFAIR: Enabling FAIR AI for HPC Applications | 0 | 0.34 | 2021 |
Simple Augmentation Goes a Long Way: ADRL for DNN Quantization | 0 | 0.34 | 2021 |
TADOC: Text analytics directly on compression | 7 | 0.45 | 2021 |
Recurrent Neural Networks Meet Context-Free Grammar: Two Birds with One Stone | 0 | 0.34 | 2021 |
UDF to SQL translation through compositional lazy inductive synthesis | 0 | 0.34 | 2021 |
Toward efficient interactions between Python and native libraries | 0 | 0.34 | 2021 |
FLEET - Flexible Efficient Ensemble Training for Heterogeneous Deep Neural Networks. | 0 | 0.34 | 2020 |
GOPipe: A Granularity-Oblivious Programming Framework for Pipelined Stencil Executions on GPU | 0 | 0.34 | 2020 |
MERR: Improving Security of Persistent Memory Objects via Efficient Memory Exposure Reduction and Randomization | 3 | 0.37 | 2020 |
Special Issue: Graph Computing | 0 | 0.34 | 2020 |
HISyn: human learning-inspired natural language programming | 1 | 0.38 | 2020 |
MKPipe: a compiler framework for optimizing multi-kernel workloads in OpenCL for FPGA | 0 | 0.34 | 2020 |
Wootz: a compiler-based framework for fast CNN pruning via composability | 1 | 0.43 | 2019 |
IA-graph based inter-app conflicts detection in open IoT systems | 0 | 0.34 | 2019 |
HiWayLib: A Software Framework for Enabling High Performance Communications for Heterogeneous Pipeline Computations | 0 | 0.34 | 2019 |
Adaptive Deep Reuse: Accelerating CNN Training on the Fly | 1 | 0.35 | 2019 |
Streamline Density Peak Clustering for Practical Adoptions | 0 | 0.34 | 2019 |
Zwift: A Programming Framework for High Performance Text Analytics on Compressed Data. | 2 | 0.38 | 2018 |
LEEM: Lean Elastic EM for Gaussian Mixture Model via Bounds-Based Filtering | 0 | 0.34 | 2018 |
Exploring flexible communications for streamlining DNN ensemble training pipelines. | 0 | 0.34 | 2018 |
LCD: A Fast Contrastive Divergence Based Algorithm for Restricted Boltzmann Machine. | 0 | 0.34 | 2018 |
Efficient document analytics on compressed data: method, challenges, algorithms, insights | 3 | 0.39 | 2018 |
Footprint Modeling Of Cache Associativity And Granularity | 0 | 0.34 | 2018 |
FALCON: A Fast Drop-In Replacement of Citation KNN for Multiple Instance Learning. | 0 | 0.34 | 2018 |
Editorial for the Special Issue on In-Memory Computing | 0 | 0.34 | 2018 |
Efficient support of position independence on non-volatile memory. | 6 | 0.43 | 2017 |
Generalizations of the theory and deployment of triangular inequality for compiler-based strength reduction. | 4 | 0.41 | 2017 |
Understanding co-run performance on CPU-GPU integrated processors: observations, insights, directions. | 1 | 0.36 | 2017 |
Data-centric combinatorial optimization of parallel code. | 3 | 0.37 | 2016 |
Coherence-Free Multiview: Enabling Reference-Discerning Data Placement on GPU. | 5 | 0.41 | 2016 |
Examining and Reducing the Influence of Sampling Errors on Feedback-Driven Optimizations. | 0 | 0.34 | 2016 |
Tuning for software analytics | 37 | 0.69 | 2016 |