Student
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Review 1
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Review 2
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Review 3
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| Sindarov, Asadbek |
H2-LLM: Hardware-Dataflow Co-Exploration for Heterogeneous Hybrid-Bonding-based Low-Batch LLM Inference |
FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving |
MPK: A Compiler and Runtime for Mega-Kernelizing Tensor Programs |
| Kazemi, Mehrafarin |
TANGRAM: Optimized Coarse-Grained Dataflow for Scalable NN Accelerators |
POD-Attention: Unlocking Full Prefill-Decode Overlap for Faster LLM Inference
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DistServe: Disaggregating Prefill
and Decoding for Goodputoptimized
Large Language Model Serving |
| Le, Hoang Dang Nguyen |
MPK: A Compiler and Runtime for Mega-Kernelizing Tensor Programs |
ARC: Warp-level Adaptive Atomic Reduction in GPUs to Accelerate Differentiable Rendering |
ThunderKittens: Simple, Fast, and Adorable AI Kernels |
| Kooshky, Amirmohammad |
Eyeriss: A Spatial Architecture for Energy-Efficient Dataflow for
Convolutional Neural Networks |
MP-Rec: Hardware-Software Co-Design to Enable Multi-Path Recommendation |
TVM: An Automated End-to-End Optimizing Compiler for Deep Learning |
| Farag, Yousef |
Efficient Memory Management for Large Language Model Serving with PagedAttention |
Orca: A Distributed Serving System for Transformer-Based Generative Models |
ARC: Warp-level Adaptive Atomic Reduction in GPUs to Accelerate Differentiable Rendering |
| Hariharan, Tarun |
POD-Attention: Unlocking Full PrefillDecode Overlap for
Faster LLM Inference |
PointAcc: Efficient Point Cloud Accelerator |
throttLL’eM: Predictive GPU Throttling for Energy Efficient LLM Inference Serving |
| Wang, Zirui |
Zeus: Understanding and Optimizing GPU Energy Consumption of DNN Training |
ELSA: Hardware-Software Co-Design for Efficient, Lightweight Self-Attention Mechanism in Neural Networks |
Efficient Memory Management for Large Language Model Serving with PagedAttention |
| Patel, Nehali Sudarshan |
ELSA: Hardware-Software Co-Design for Efficient, Lightweight Self-Attention Mechanism in Neural Networks |
FlashInfer: Efficient and Customizable Attention Engine for LLM Inference Serving |
AttAcc! Unleashing the Power of PIM for Batched Transformer-based Generative Model Inference |
| K.A., Abdul Manan |
WLB-LLM: Workload-Balanced 4D Parallelism for Large Language Model Training |
FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness |
ZeRO: Memory Optimizations Toward Training Trillion Parameter Models |
| Subedi, Ashish |
H2-LLM: Hardware-Dataflow Co-Exploration for Heterogeneous Hybrid-Bonding-based Low-Batch LLM Inference |
Efficient Large-Scale Language Model Training on GPU Clusters Using Megatron-LM |
DynamoLLM: Designing LLM Inference Clusters for Performance and Energy Efficiency |
| Suntoro, Marcellius William |
H2-LLM: Hardware-Dataflow Co-Exploration for Heterogeneous Hybrid-Bonding-based Low-Batch
LLM Inference |
Orca: A Distributed Serving System for Transformer-Based Generative Models |
NanoFlow: Towards Optimal Large Language Model Serving Throughput |
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