Saved in:
| Main Authors: | Wang, Haonan, Xiao, Xuxin, Yan, Mingyu, Zhu, Zhuoyuan, Han, Dengke, Wang, Duo, Li, Wenming, Ye, Xiaochun, Hu, Cunchen, Chen, Hongyang, Sun, Guangyu |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2512.01644 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
TLV-HGNN: Thinking Like a Vertex for Memory-efficient HGNN Inference
by: Han, Dengke, et al.
Published: (2025)
by: Han, Dengke, et al.
Published: (2025)
Characterizing and Understanding HGNN Training on GPUs
by: Han, Dengke, et al.
Published: (2024)
by: Han, Dengke, et al.
Published: (2024)
Accelerating GNN Training through Locality-aware Dropout and Merge
by: Sun, Gongjian, et al.
Published: (2025)
by: Sun, Gongjian, et al.
Published: (2025)
HiHGNN: Accelerating HGNNs through Parallelism and Data Reusability Exploitation
by: Xue, Runzhen, et al.
Published: (2023)
by: Xue, Runzhen, et al.
Published: (2023)
Survey on Characterizing and Understanding GNNs from a Computer Architecture Perspective
by: Wu, Meng, et al.
Published: (2024)
by: Wu, Meng, et al.
Published: (2024)
ADE-HGNN: Accelerating HGNNs through Attention Disparity Exploitation
by: Han, Dengke, et al.
Published: (2024)
by: Han, Dengke, et al.
Published: (2024)
GDR-HGNN: A Heterogeneous Graph Neural Networks Accelerator Frontend with Graph Decoupling and Recoupling
by: Xue, Runzhen, et al.
Published: (2024)
by: Xue, Runzhen, et al.
Published: (2024)
SiHGNN: Leveraging Properties of Semantic Graphs for Efficient HGNN Acceleration
by: Xue, Runzhen, et al.
Published: (2024)
by: Xue, Runzhen, et al.
Published: (2024)
Accelerating Mini-batch HGNN Training by Reducing CUDA Kernels
by: Wu, Meng, et al.
Published: (2024)
by: Wu, Meng, et al.
Published: (2024)
Multi-objective Optimization in CPU Design Space Exploration: Attention is All You Need
by: Xue, Runzhen, et al.
Published: (2024)
by: Xue, Runzhen, et al.
Published: (2024)
MetaDSE: A Few-shot Meta-learning Framework for Cross-workload CPU Design Space Exploration
by: Xue, Runzhen, et al.
Published: (2025)
by: Xue, Runzhen, et al.
Published: (2025)
StreamDCIM: A Tile-based Streaming Digital CIM Accelerator with Mixed-stationary Cross-forwarding Dataflow for Multimodal Transformer
by: Qin, Shantian, et al.
Published: (2025)
by: Qin, Shantian, et al.
Published: (2025)
AHASD: Asynchronous Heterogeneous Architecture for LLM Adaptive Drafting Speculative Decoding on Mobile Devices
by: Zirui, Ma, et al.
Published: (2026)
by: Zirui, Ma, et al.
Published: (2026)
Ouroboros: Wafer-Scale SRAM CIM with Token-Grained Pipelining for Large Language Model Inference
by: Liu, Yiqi, et al.
Published: (2026)
by: Liu, Yiqi, et al.
Published: (2026)
Multilayer Dataflow: Orchestrate Butterfly Sparsity to Accelerate Attention Computation
by: Wu, Haibin, et al.
Published: (2024)
by: Wu, Haibin, et al.
Published: (2024)
METRO: A Software-Hardware Co-Design of Interconnections for Spatial DNN Accelerators
by: Wang, Zhao, et al.
Published: (2021)
by: Wang, Zhao, et al.
Published: (2021)
Topkima-Former: Low-energy, Low-Latency Inference for Transformers using top-k In-memory ADC
by: Dong, Shuai, et al.
Published: (2024)
by: Dong, Shuai, et al.
Published: (2024)
Mixed Structural Choice Operator: Enhancing Technology Mapping with Heterogeneous Representations
by: Hu, Zhang, et al.
Published: (2025)
by: Hu, Zhang, et al.
Published: (2025)
CarbonSet: A Dataset to Analyze Trends and Benchmark the Sustainability of CPUs and GPUs
by: Hu, Jiajun, et al.
Published: (2025)
by: Hu, Jiajun, et al.
Published: (2025)
Control Flow Management in Modern GPUs
by: Shoushtary, Mojtaba Abaie, et al.
Published: (2024)
by: Shoushtary, Mojtaba Abaie, et al.
Published: (2024)
Virgo: Cluster-level Matrix Unit Integration in GPUs for Scalability and Energy Efficiency
by: Kim, Hansung, et al.
Published: (2024)
by: Kim, Hansung, et al.
Published: (2024)
CoverAssert: Iterative LLM Assertion Generation Driven by Functional Coverage via Syntax-Semantic Representations
by: Wang, Yonghao, et al.
Published: (2026)
by: Wang, Yonghao, et al.
Published: (2026)
3D Stack In-Sensor-Computing (3DS-ISC): Accelerating Time-Surface Construction for Neuromorphic Event Cameras
by: Shang, Hongyang, et al.
Published: (2025)
by: Shang, Hongyang, et al.
Published: (2025)
Privacy-Preserving Performance Profiling of In-The-Wild GPUs
by: McDougall, Ian, et al.
Published: (2025)
by: McDougall, Ian, et al.
Published: (2025)
MCBP: A Memory-Compute Efficient LLM Inference Accelerator Leveraging Bit-Slice-enabled Sparsity and Repetitiveness
by: Wang, Huizheng, et al.
Published: (2025)
by: Wang, Huizheng, et al.
Published: (2025)
AssertGen: Enhancement of LLM-aided Assertion Generation through Cross-Layer Signal Bridging
by: Lyu, Hongqin, et al.
Published: (2025)
by: Lyu, Hongqin, et al.
Published: (2025)
SpeedLLM: An FPGA Co-design of Large Language Model Inference Accelerator
by: Wang, Peipei, et al.
Published: (2025)
by: Wang, Peipei, et al.
Published: (2025)
EdgeReasoning: Characterizing Reasoning LLM Deployment on Edge GPUs
by: Kubwimana, Benjamin, et al.
Published: (2025)
by: Kubwimana, Benjamin, et al.
Published: (2025)
LLM-PRISM: Characterizing Silent Data Corruption from Permanent GPU Faults in LLM Training
by: Tyagi, Abhishek, et al.
Published: (2026)
by: Tyagi, Abhishek, et al.
Published: (2026)
CADC: Crossbar-Aware Dendritic Convolution for Efficient In-memory Computing
by: Dong, Shuai, et al.
Published: (2025)
by: Dong, Shuai, et al.
Published: (2025)
NVLLM: A 3D NAND-Centric Architecture Enabling Edge on-Device LLM Inference
by: Hao, Mingbo, et al.
Published: (2026)
by: Hao, Mingbo, et al.
Published: (2026)
Comparative Characterization of KV Cache Management Strategies for LLM Inference
by: Mamo, Oteo, et al.
Published: (2026)
by: Mamo, Oteo, et al.
Published: (2026)
Bandwidth-Effective DRAM Cache for GPUs with Storage-Class Memory
by: Hong, Jeongmin, et al.
Published: (2024)
by: Hong, Jeongmin, et al.
Published: (2024)
PRIMAL: Processing-In-Memory Based Low-Rank Adaptation for LLM Inference Accelerator
by: Chong, Yue Jiet, et al.
Published: (2026)
by: Chong, Yue Jiet, et al.
Published: (2026)
Pushing the Limits of BFP on Narrow Precision LLM Inference
by: Wang, Hui, et al.
Published: (2025)
by: Wang, Hui, et al.
Published: (2025)
FusionCIM: Accelerating LLM Inference with Fusion-Driven Computing-in-Memory Architecture
by: Xuan, Zihao, et al.
Published: (2026)
by: Xuan, Zihao, et al.
Published: (2026)
Accelerating MoE with Dynamic In-Switch Computing on Multi-GPUs
by: Zhang, Qijun, et al.
Published: (2026)
by: Zhang, Qijun, et al.
Published: (2026)
Near-Memory Architecture for Threshold-Ordinal Surface-Based Corner Detection of Event Cameras
by: Shang, Hongyang, et al.
Published: (2025)
by: Shang, Hongyang, et al.
Published: (2025)
Cambricon-LLM: A Chiplet-Based Hybrid Architecture for On-Device Inference of 70B LLM
by: Yu, Zhongkai, et al.
Published: (2024)
by: Yu, Zhongkai, et al.
Published: (2024)
Hardware-Software Co-design for 3D-DRAM-based LLM Serving Accelerator
by: Li, Cong, et al.
Published: (2026)
by: Li, Cong, et al.
Published: (2026)
Similar Items
-
TLV-HGNN: Thinking Like a Vertex for Memory-efficient HGNN Inference
by: Han, Dengke, et al.
Published: (2025) -
Characterizing and Understanding HGNN Training on GPUs
by: Han, Dengke, et al.
Published: (2024) -
Accelerating GNN Training through Locality-aware Dropout and Merge
by: Sun, Gongjian, et al.
Published: (2025) -
HiHGNN: Accelerating HGNNs through Parallelism and Data Reusability Exploitation
by: Xue, Runzhen, et al.
Published: (2023) -
Survey on Characterizing and Understanding GNNs from a Computer Architecture Perspective
by: Wu, Meng, et al.
Published: (2024)