{"total":39,"rows":[{"id":"2102.00075","title":"RecSSD: Near Data Processing for Solid State Drive Based Recommendation Inference","created":"2021-01-29","cited_by_count":35,"area":null},{"id":"2209.10117","title":"A Comprehensive Survey on Trustworthy Recommender Systems","created":"2022-09-21","cited_by_count":32,"area":null},{"id":"2406.12930","title":"Tender: Accelerating Large Language Models via Tensor Decomposition and Runtime Requantization","created":"2024-06-16","cited_by_count":28,"area":null},{"id":"2403.06664","title":"Smart-Infinity: Fast Large Language Model Training using Near-Storage Processing on a Real System","created":"2024-03-11","cited_by_count":15,"area":null},{"id":"2310.02784","title":"MAD Max Beyond Single-Node: Enabling Large Machine Learning Model Acceleration on Distributed Systems","created":"2023-10-04","cited_by_count":14,"area":null},{"id":"2204.05436","title":"Heterogeneous Acceleration Pipeline for Recommendation System Training","created":"2022-04-11","cited_by_count":13,"area":null},{"id":"2205.04711","title":"SmartSAGE: Training Large-scale Graph Neural Networks using In-Storage Processing Architectures","created":"2022-05-10","cited_by_count":13,"area":null},{"id":"2209.00606","title":"Sparse Attention Acceleration with Synergistic In-Memory Pruning and On-Chip Recomputation","created":"2022-09-01","cited_by_count":12,"area":null},{"id":"2205.04702","title":"Training Personalized Recommendation Systems from (GPU) Scratch: Look Forward not Backwards","created":"2022-05-10","cited_by_count":11,"area":null},{"id":"2102.07511","title":"GradPIM: A Practical Processing-in-DRAM Architecture for Gradient Descent","created":"2021-02-15","cited_by_count":10,"area":null},{"id":"2310.09443","title":"G10: Enabling An Efficient Unified GPU Memory and Storage Architecture with Smart Tensor Migrations","created":"2023-10-13","cited_by_count":10,"area":null},{"id":"2302.10872","title":"MP-Rec: Hardware-Software Co-Design to Enable Multi-Path Recommendation","created":"2023-02-21","cited_by_count":9,"area":null},{"id":"2105.08820","title":"RecPipe: Co-designing Models and Hardware to Jointly Optimize Recommendation Quality and Performance","created":"2021-05-18","cited_by_count":8,"area":null},{"id":"2111.00680","title":"GNNear: Accelerating Full-Batch Training of Graph Neural Networks with Near-Memory Processing","created":"2021-11-01","cited_by_count":6,"area":null},{"id":"2305.05766","title":"Instant-NeRF: Instant On-Device Neural Radiance Field Training via Algorithm-Accelerator Co-Designed Near-Memory Processing","created":"2023-05-09","cited_by_count":6,"area":null},{"id":"2203.00158","title":"GROW: A Row-Stationary Sparse-Dense GEMM Accelerator for Memory-Efficient Graph Convolutional Neural Networks","created":"2022-03-01","cited_by_count":5,"area":null},{"id":"2404.07164","title":"PIM-Opt: Demystifying Distributed Optimization Algorithms on a Real-World Processing-In-Memory System","created":"2024-04-10","cited_by_count":5,"area":null},{"id":"2208.12392","title":"DiVa: An Accelerator for Differentially Private Machine Learning","created":"2022-08-26","cited_by_count":4,"area":null},{"id":"2312.11742","title":"ACCL+: an FPGA-Based Collective Engine for Distributed Applications","created":"2023-12-18","cited_by_count":3,"area":null},{"id":"2402.16731","title":"PyGim: An Efficient Graph Neural Network Library for Real Processing-In-Memory Architectures","created":"2024-02-26","cited_by_count":3,"area":null},{"id":"2509.20979","title":"Toward Robust and Efficient ML-Based GPU Caching for Modern Inference","created":"2025-09-25","cited_by_count":3,"area":null},{"id":"2207.07886","title":"An Experimental Evaluation of Machine Learning Training on a Real Processing-in-Memory System","created":"2022-07-16","cited_by_count":2,"area":null},{"id":"2406.14571","title":"PreSto: An In-Storage Data Preprocessing System for Training Recommendation Models","created":"2024-06-11","cited_by_count":2,"area":null},{"id":"2501.00210","title":"Debunking the CUDA Myth Towards GPU-based AI Systems","created":"2024-12-31","cited_by_count":2,"area":null},{"id":"2202.02310","title":"EcoFlow: Efficient Convolutional Dataflows for Low-Power Neural Network Accelerators","created":"2022-02-04","cited_by_count":1,"area":null},{"id":"2205.14664","title":"Heterogeneous Data-Centric Architectures for Modern Data-Intensive Applications: Case Studies in Machine Learning and Databases","created":"2022-05-29","cited_by_count":1,"area":null},{"id":"2301.07492","title":"Failure Tolerant Training with Persistent Memory Disaggregation over CXL","created":"2023-01-14","cited_by_count":1,"area":null},{"id":"2409.16633","title":"PIFS-Rec: Process-In-Fabric-Switch for Large-Scale Recommendation System Inferences","created":"2024-09-25","cited_by_count":1,"area":null},{"id":"2410.12794","title":"Disaggregating Embedding Recommendation Systems with FlexEMR","created":"2024-09-28","cited_by_count":1,"area":null},{"id":"2510.07304","title":"Cocoon: A System Architecture for Differentially Private Training with Correlated Noises","created":"2025-10-08","cited_by_count":1,"area":null},{"id":"2604.04523","title":"LOCALUT: Harnessing Capacity-Computation Tradeoffs for LUT-Based Inference in DRAM-PIM","created":"2026-04-06","cited_by_count":1,"area":null},{"id":"2104.13671","title":"Continual Learning Approach for Improving the Data and Computation Mapping in Near-Memory Processing System","created":"2021-04-28","cited_by_count":0,"area":null},{"id":"2302.11750","title":"Hera: A Heterogeneity-Aware Multi-Tenant Inference Server for Personalized Recommendations","created":"2023-02-23","cited_by_count":0,"area":null},{"id":"2402.04032","title":"ProactivePIM: Accelerating Weight-Sharing Embedding Layer with PIM for Scalable Recommendation System","created":"2024-02-06","cited_by_count":0,"area":null},{"id":"2406.06955","title":"ElasticRec: A Microservice-based Model Serving Architecture Enabling Elastic Resource Scaling for Recommendation Models","created":"2024-06-11","cited_by_count":0,"area":null},{"id":"2410.07928","title":"The Function-Representation Model of Computation","created":"2024-10-10","cited_by_count":0,"area":null},{"id":"2410.22249","title":"Pushing the Performance Envelope of DNN-based Recommendation Systems Inference on GPUs","created":"2024-10-29","cited_by_count":0,"area":null},{"id":"2504.00520","title":"SCRec: A Scalable Computational Storage System with Statistical Sharding and Tensor-train Decomposition for Recommendation Models","created":"2025-04-01","cited_by_count":0,"area":null},{"id":"2511.15503","title":"DCC: Data-Centric Compilation of Machine Learning Kernels for Processing-In-Memory Architectures","created":"2025-11-19","cited_by_count":0,"area":null}],"next_cursor":null}