Pre-gated MoE: An Algorithm-System Co-Design for Fast and Scalable Mixture-of-Expert Inference
Fuente:
arXiv
Saved in:
| Main Authors: | Hwang, Ranggi, Wei, Jianyu, Cao, Shijie, Hwang, Changho, Tang, Xiaohu, Cao, Ting, Yang, Mao |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
PASCAL: A Phase-Aware Scheduling Algorithm for Serving Reasoning-based Large Language Models
by: Cho, Eunyeong, et al.
Published: (2026)
by: Cho, Eunyeong, et al.
Published: (2026)
T-MAN: Enabling End-to-End Low-Bit LLM Inference on NPUs via Unified Table Lookup
by: Wei, Jianyu, et al.
Published: (2025)
by: Wei, Jianyu, et al.
Published: (2025)
SliceMoE: Bit-Sliced Expert Caching under Miss-Rate Constraints for Efficient MoE Inference
by: Choi, Yuseon, et al.
Published: (2025)
by: Choi, Yuseon, et al.
Published: (2025)
A3D-MoE: Acceleration of Large Language Models with Mixture of Experts via 3D Heterogeneous Integration
by: Huang, Wei-Hsing, et al.
Published: (2025)
by: Huang, Wei-Hsing, et al.
Published: (2025)
Expert Streaming: Accelerating Low-Batch MoE Inference via Multi-chiplet Architecture and Dynamic Expert Trajectory Scheduling
by: Ma, Songchen, et al.
Published: (2026)
by: Ma, Songchen, et al.
Published: (2026)
MoE-GPS: Guidlines for Prediction Strategy for Dynamic Expert Duplication in MoE Load Balancing
by: Ma, Haiyue, et al.
Published: (2025)
by: Ma, Haiyue, et al.
Published: (2025)
TENET: An Efficient Sparsity-Aware LUT-Centric Architecture for Ternary LLM Inference On Edge
by: Huang, Zhirui, et al.
Published: (2025)
by: Huang, Zhirui, et al.
Published: (2025)
CoQMoE: Co-Designed Quantization and Computation Orchestration for Mixture-of-Experts Vision Transformer on FPGA
by: Dong, Jiale, et al.
Published: (2025)
by: Dong, Jiale, et al.
Published: (2025)
CogSys: Efficient and Scalable Neurosymbolic Cognition System via Algorithm-Hardware Co-Design
by: Wan, Zishen, et al.
Published: (2025)
by: Wan, Zishen, et al.
Published: (2025)
Mozart: Modularized and Efficient MoE Training on 3.5D Wafer-Scale Chiplet Architectures
by: Luo, Shuqing, et al.
Published: (2026)
by: Luo, Shuqing, et al.
Published: (2026)
UbiMoE: A Ubiquitous Mixture-of-Experts Vision Transformer Accelerator With Hybrid Computation Pattern on FPGA
by: Dong, Jiale, et al.
Published: (2025)
by: Dong, Jiale, et al.
Published: (2025)
Harmonia: Algorithm-Hardware Co-Design for Memory- and Compute-Efficient BFP-based LLM Inference
by: Wang, Xinyu, et al.
Published: (2026)
by: Wang, Xinyu, et al.
Published: (2026)
Context-Aware Mixture-of-Experts Inference on CXL-Enabled GPU-NDP Systems
by: Fan, Zehao, et al.
Published: (2025)
by: Fan, Zehao, et al.
Published: (2025)
Hardware-based Heterogeneous Memory Management for Large Language Model Inference
by: Hwang, Soojin, et al.
Published: (2025)
by: Hwang, Soojin, et al.
Published: (2025)
CRYPTONITE: Scalable Accelerator Design for Cryptographic Primitives and Algorithms
by: Maheswaran, Karthikeya Sharma, et al.
Published: (2025)
by: Maheswaran, Karthikeya Sharma, et al.
Published: (2025)
LUT Tensor Core: A Software-Hardware Co-Design for LUT-Based Low-Bit LLM Inference
by: Mo, Zhiwen, et al.
Published: (2024)
by: Mo, Zhiwen, et al.
Published: (2024)
Sieve: Dynamic Expert-Aware PIM Acceleration for Evolving Mixture-of-Experts Models
by: Kim, Jungwoo, et al.
Published: (2026)
by: Kim, Jungwoo, et al.
Published: (2026)
Stratum: System-Hardware Co-Design with Tiered Monolithic 3D-Stackable DRAM for Efficient MoE Serving
by: Pan, Yue, et al.
Published: (2025)
by: Pan, Yue, et al.
Published: (2025)
Scaling Multi-Node Mixture-of-Experts Inference Using Expert Activation Patterns
by: Bambhaniya, Abhimanyu, et al.
Published: (2026)
by: Bambhaniya, Abhimanyu, et al.
Published: (2026)
NASiC: 3D NAND-based CAM-Selected Multibit CIM Architecture for Efficient On-Device Mixture-of-Experts LLM Inference
by: Xu, Weikai, et al.
Published: (2026)
by: Xu, Weikai, et al.
Published: (2026)
AxMoE: Characterizing the Impact of Approximate Multipliers on Mixture-of-Experts DNN Architectures
by: Shende, Omkar B, et al.
Published: (2026)
by: Shende, Omkar B, et al.
Published: (2026)
Rethinking LLM Inference Bottlenecks: Insights from Latent Attention and Mixture-of-Experts
by: Yun, Sungmin, et al.
Published: (2025)
by: Yun, Sungmin, et al.
Published: (2025)
Efficient MoE Serving in the Memory-Bound Regime: Balance Activated Experts, Not Tokens
by: Yu, Yanpeng, et al.
Published: (2025)
by: Yu, Yanpeng, et al.
Published: (2025)
Area-Efficient In-Memory Computing for Mixture-of-Experts via Multiplexing and Caching
by: Gao, Hanyuan, et al.
Published: (2026)
by: Gao, Hanyuan, et al.
Published: (2026)
STI-SNN: A 0.14 GOPS/W/PE Single-Timestep Inference FPGA-based SNN Accelerator with Algorithm and Hardware Co-Design
by: Wang, Kainan, et al.
Published: (2025)
by: Wang, Kainan, et al.
Published: (2025)
Hardware-Software Co-Design for Accelerating Transformer Inference Leveraging Compute-in-Memory
by: Kim, Dong Eun, et al.
Published: (2025)
by: Kim, Dong Eun, et al.
Published: (2025)
MoE-Hub: Taming Software Complexity for Seamless MoE Overlap with Hardware-Accelerated Communication on Multi-GPU Systems
by: Zhou, Zhuoshan, et al.
Published: (2026)
by: Zhou, Zhuoshan, et al.
Published: (2026)
SSD Offloading for LLM Mixture-of-Experts Weights Considered Harmful in Energy Efficiency
by: Kyung, Kwanhee, et al.
Published: (2025)
by: Kyung, Kwanhee, et al.
Published: (2025)
BitDecoding: Unlocking Tensor Cores for Long-Context LLMs with Low-Bit KV Cache
by: Du, Dayou, et al.
Published: (2025)
by: Du, Dayou, et al.
Published: (2025)
MixDiT: Accelerating Image Diffusion Transformer Inference with Mixed-Precision MX Quantization
by: Kim, Daeun, et al.
Published: (2025)
by: Kim, Daeun, et al.
Published: (2025)
MX-SAFE: Versatile Inference- and Training-Proof Microscaling Format with On-the-Fly Exponent and Mantissa Bit Allocation
by: Park, Dahoon, et al.
Published: (2026)
by: Park, Dahoon, et al.
Published: (2026)
FlashMoE: Fast Distributed MoE in a Single Kernel
by: Aimuyo, Osayamen Jonathan, et al.
Published: (2025)
by: Aimuyo, Osayamen Jonathan, et al.
Published: (2025)
Hecaton: Training Large Language Models with Scalable Chiplet Systems
by: Huang, Zongle, et al.
Published: (2024)
by: Huang, Zongle, et al.
Published: (2024)
AraXL: A Physically Scalable, Ultra-Wide RISC-V Vector Processor Design for Fast and Efficient Computation on Long Vectors
by: Purayil, Navaneeth Kunhi, et al.
Published: (2025)
by: Purayil, Navaneeth Kunhi, et al.
Published: (2025)
MemExplorer: Navigating the Heterogeneous Memory Design Space for Agentic Inference NPUs
by: Wu, Haoran, et al.
Published: (2026)
by: Wu, Haoran, et al.
Published: (2026)
Mixture of Cache-Conditional Experts for Efficient Mobile Device Inference
by: Skliar, Andrii, et al.
Published: (2024)
by: Skliar, Andrii, et al.
Published: (2024)
GenPairX: A Hardware-Algorithm Co-Designed Accelerator for Paired-End Read Mapping
by: Eudine, Julien, et al.
Published: (2026)
by: Eudine, Julien, et al.
Published: (2026)
LoopLynx: A Scalable Dataflow Architecture for Efficient LLM Inference
by: Zheng, Jianing, et al.
Published: (2025)
by: Zheng, Jianing, et al.
Published: (2025)
APSQ: Additive Partial Sum Quantization with Algorithm-Hardware Co-Design
by: Tan, Yonghao, et al.
Published: (2025)
by: Tan, Yonghao, et al.
Published: (2025)
MoNDE: Mixture of Near-Data Experts for Large-Scale Sparse Models
by: Kim, Taehyun, et al.
Published: (2024)
by: Kim, Taehyun, et al.
Published: (2024)
Similar Items
-
PASCAL: A Phase-Aware Scheduling Algorithm for Serving Reasoning-based Large Language Models
by: Cho, Eunyeong, et al.
Published: (2026) -
T-MAN: Enabling End-to-End Low-Bit LLM Inference on NPUs via Unified Table Lookup
by: Wei, Jianyu, et al.
Published: (2025) -
SliceMoE: Bit-Sliced Expert Caching under Miss-Rate Constraints for Efficient MoE Inference
by: Choi, Yuseon, et al.
Published: (2025) -
A3D-MoE: Acceleration of Large Language Models with Mixture of Experts via 3D Heterogeneous Integration
by: Huang, Wei-Hsing, et al.
Published: (2025) -
Expert Streaming: Accelerating Low-Batch MoE Inference via Multi-chiplet Architecture and Dynamic Expert Trajectory Scheduling
by: Ma, Songchen, et al.
Published: (2026)