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Multi-GPU System Design with Memory Networks
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/978-3-642-03869-3_79openalex-snapshot
An Extension of the StarSs Programming Model for Platforms with Multiple GPUs
inferredcites →https://doi.org/10.1016/b978-0-12-416970-8.00004-3openalex-snapshot
Multi-GPU Programming
inferredcites →https://doi.org/10.1109/hotchips.2011.7477494openalex-snapshot
Hybrid memory cube (HMC)
inferredcites →https://doi.org/10.1109/hoti.2010.24openalex-snapshot
Intel® QuickPath Interconnect Architectural Features Supporting Scalable System Architectures
inferredcites →https://doi.org/10.1109/hpca.2013.6522351openalex-snapshot
Cache coherence for GPU architectures
inferredcites →https://doi.org/10.1109/iiswc.2009.5306797openalex-snapshot
Rodinia: A benchmark suite for heterogeneous computing
inferredcites →https://doi.org/10.1109/iiswc.2012.6402918openalex-snapshot
A quantitative study of irregular programs on GPUs
inferredcites →https://doi.org/10.1109/ipdps.2009.5161068openalex-snapshot
Exploring the multiple-GPU design space
inferredcites →https://doi.org/10.1109/ipdpsw.2010.5470941openalex-snapshot
Dense linear algebra solvers for multicore with GPU accelerators
inferredcites →https://doi.org/10.1109/isca.2005.35openalex-snapshot
Microarchitecture of a High-Radix Router
inferredcites →https://doi.org/10.1109/isca.2012.6237034openalex-snapshot
Buffer-on-board memory systems
inferredcites →https://doi.org/10.1109/ispa.2011.28openalex-snapshot
Hybrid OpenCL: Enhancing OpenCL for Distributed Processing
inferredcites →https://doi.org/10.1109/ispa.2012.100openalex-snapshot
Static Multi-device Load Balancing for OpenCL
inferredcites →https://doi.org/10.1109/ispass.2009.4919648openalex-snapshot
Analyzing CUDA workloads using a detailed GPU simulator
inferredcites →https://doi.org/10.1109/ispass.2013.6557148openalex-snapshot
McSimA+: A manycore simulator with application-level+ simulation and detailed microarchitecture modeling
inferredcites →https://doi.org/10.1109/ispass.2013.6557149openalex-snapshot
A detailed and flexible cycle-accurate Network-on-Chip simulator
inferredcites →https://doi.org/10.1109/mascots.2013.77openalex-snapshot
DistCL: A Framework for the Distributed Execution of OpenCL Kernels
inferredcites →https://doi.org/10.1109/mm.2014.4openalex-snapshot
Cache Coherence for GPU Architectures
inferredcites →https://doi.org/10.1109/pact.2013.6618805openalex-snapshot
Memory-centric system interconnect design with hybrid memory cubes
inferredcites →https://doi.org/10.1109/pact.2013.6618812openalex-snapshot
Memory-centric system interconnect design with Hybrid Memory Cubes
inferredcites →https://doi.org/10.1109/pact.2013.6618814openalex-snapshot
Transparent CPU-GPU collaboration for data-parallel kernels on heterogeneous systems
inferredcites →https://doi.org/10.1117/12.921122openalex-snapshot
ArrayFire: a GPU acceleration platform
inferredcites →https://doi.org/10.1145/1080695.1070005openalex-snapshot
Microarchitecture of a High-Radix Router
inferredcites →https://doi.org/10.1145/1105734.1105747openalex-snapshot
Multifacet's general execution-driven multiprocessor simulator (GEMS) toolset
inferredcites →https://doi.org/10.1145/1941553.1941591openalex-snapshot
Achieving a single compute device image in OpenCL for multiple GPUs
inferredcites →https://doi.org/10.1145/2366231.2337204openalex-snapshot
Buffer-on-board memory systems
inferredcites →https://doi.org/10.1177/109434209100500306openalex-snapshot
The NAS Parallel Benchmarks
inferredcites →https://doi.org/10.12694/scpe.v11i3.654openalex-snapshot
Programming Massively Parallel Processors. A Hands-on Approach
inferredcites →https://doi.org/10.26053/0h-tqhf-9100openalex-snapshot
Data placement for efficient main memory access
inferredcites →https://doi.org/10.5555/2386173.2386183openalex-snapshot
CUDASA: compute unified device and systems architecture
inferredcites →https://doi.org/10.5555/2523721.2523756openalex-snapshot
Transparent CPU-GPU collaboration for data-parallel kernels on heterogeneous systems
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-030-79478-1_13openalex-snapshot
Dynamic GMMU Bypass for Address Translation in Multi-GPU Systems
inferred← citeshttps://doi.org/10.1007/978-3-031-01763-6openalex-snapshot
Innovations in the Memory System
inferred← citeshttps://doi.org/10.1007/978-3-319-21909-7_44openalex-snapshot
Performance Evaluation of a Human Immune System Simulator on a GPU Cluster
inferred← citeshttps://doi.org/10.1007/978-3-319-95162-1_11openalex-snapshot
Inferring Gene Regulatory Networks Using Hybrid Parallel Computing
inferred← citeshttps://doi.org/10.1016/j.jpdc.2018.11.012openalex-snapshot
A survey of architectural approaches for improving GPGPU performance, programmability and heterogeneity
inferred← citeshttps://doi.org/10.1016/j.parco.2026.103208openalex-snapshot
A comprehensive survey on multi-GPU systems
inferred← citeshttps://doi.org/10.1109/access.2022.3195271openalex-snapshot
Demand MemCpy: Overlapping of Computation and Data Transfer for Heterogeneous Computing
inferred← citeshttps://doi.org/10.1109/hipc.2018.00041openalex-snapshot
Share-a-GPU: Providing Simple and Effective Time-Sharing on GPUs
inferred← citeshttps://doi.org/10.1109/hpca.2017.60openalex-snapshot
Understanding and Optimizing Power Consumption in Memory Networks
inferred← citeshttps://doi.org/10.1109/hpca.2019.00016openalex-snapshot
String Figure: A Scalable and Elastic Memory Network Architecture
inferred← citeshttps://doi.org/10.1109/hpca47549.2020.00055openalex-snapshot
Griffin: Hardware-Software Support for Efficient Page Migration in Multi-GPU Systems
inferred← citeshttps://doi.org/10.1109/hpca53966.2022.00018openalex-snapshot
Enabling Efficient Large-Scale Deep Learning Training with Cache Coherent Disaggregated Memory Systems
inferred← citeshttps://doi.org/10.1109/hpca57654.2024.00025openalex-snapshot
Supporting Secure Multi-GPU Computing with Dynamic and Batched Metadata Management
inferred← citeshttps://doi.org/10.1109/hpca61900.2025.00116openalex-snapshot
PIMnet: A Domain-Specific Network for Efficient Collective Communication in Scalable PIM
inferred← citeshttps://doi.org/10.1109/iccad51958.2021.9643503openalex-snapshot
ScaleDNN: Data Movement Aware DNN Training on Multi-GPU
inferred← citeshttps://doi.org/10.1109/iccd.2015.7357093openalex-snapshot
DLB: Dynamic lane borrowing for improving bandwidth and performance in Hybrid Memory Cube
inferred← citeshttps://doi.org/10.1109/iccd.2016.7753258openalex-snapshot
Scalable memory fabric for silicon interposer-based multi-core systems
inferred← citeshttps://doi.org/10.1109/iiswc.2018.8573483openalex-snapshot
Tartan: Evaluating Modern GPU Interconnect via a Multi-GPU Benchmark Suite
inferred← citeshttps://doi.org/10.1109/intelcis.2015.7397284openalex-snapshot
A survey of techniques for warp scheduling in GPUs
inferred← citeshttps://doi.org/10.1109/ipdps.2019.00075openalex-snapshot
Exploiting Adaptive Data Compression to Improve Performance and Energy-Efficiency of Compute Workloads in Multi-GPU Systems
inferred← citeshttps://doi.org/10.1109/ipdpsw59300.2023.00015openalex-snapshot
A Task Based Approach for Co-Scheduling Ensemble Workloads on Heterogeneous Nodes
inferred← citeshttps://doi.org/10.1109/isca52012.2021.00077openalex-snapshot
Ghost Routing to Enable Oblivious Computation on Memory-centric Networks
inferred← citeshttps://doi.org/10.1109/iscas.2016.7539094openalex-snapshot
Crosstalk avoidance code for direct pass-through architecture
inferred← citeshttps://doi.org/10.1109/lca.2018.2823302openalex-snapshot
A Case for Memory-Centric HPC System Architecture for Training Deep Neural Networks
inferred← citeshttps://doi.org/10.1109/micro.2016.7783732openalex-snapshot
A unified memory network architecture for in-memory computing in commodity servers
inferred← citeshttps://doi.org/10.1109/micro.2018.00021openalex-snapshot
Beyond the Memory Wall: A Case for Memory-Centric HPC System for Deep Learning
inferred← citeshttps://doi.org/10.1109/micro.2018.00061openalex-snapshot
Multi-dimensional Parallel Training of Winograd Layer on Memory-Centric Architecture
inferred← citeshttps://doi.org/10.1109/pdp.2016.18openalex-snapshot
Randomizing Packet Memory Networks for Low-Latency Processor-Memory Communication
inferred← citeshttps://doi.org/10.1109/tc.2019.2906869openalex-snapshot
CD-Xbar: A Converge-Diverge Crossbar Network for High-Performance GPUs
inferred← citeshttps://doi.org/10.1109/tpds.2019.2928289openalex-snapshot
Evaluating Modern GPU Interconnect: PCIe, NVLink, NV-SLI, NVSwitch and GPUDirect
inferred← citeshttps://doi.org/10.1145/3300053.3319420openalex-snapshot
Quantifying the NUMA Behavior of Partitioned GPGPU Applications
inferred← citeshttps://doi.org/10.1145/3329867openalex-snapshot
Optimal Schedule for All-to-All Personalized Communication in Multiprocessor Systems
inferred← citeshttps://doi.org/10.1145/3340109openalex-snapshot
Energy Efficient Chip-to-Chip Wireless Interconnection for Heterogeneous Architectures
inferred← citeshttps://doi.org/10.1145/3559009.3569649openalex-snapshot
Locality-Aware Optimizations for Improving Remote Memory Latency in Multi-GPU Systems
inferred← citeshttps://doi.org/10.1147/jrd.2019.2963637openalex-snapshot
Redefining IBM power system design for CORAL
inferred← citeshttps://doi.org/10.1155/2022/3485505openalex-snapshot
GPU‐Based In Situ Visualization for Large‐Scale Discrete Element Simulations
inferred← citeshttps://doi.org/10.1360/n112016-00147openalex-snapshot
Emerging High-Performance Computing Systems and Technology
inferred← citeshttps://doi.org/10.17760/d20251225openalex-snapshot
Improving the global memory efficiency in GPU-based systems
inferred← citeshttps://doi.org/10.17760/d20385563openalex-snapshot
Enabling collaborative heterogeneous computing
inferred← citeshttps://doi.org/10.17760/d20416796openalex-snapshot
Improving the virtual memory efficiency of GPUs
inferred← citeshttps://doi.org/10.2200/s00933ed1v01y201906cac048openalex-snapshot
Innovations in the Memory System
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