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Compiler for FL (computation+communication)
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Is it possible to adopt imitation learning or other IRL approaches to mimic DNN compiler generated kernels,,, shortening long tuning process, boosting cross-device compiling?
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NeRF, Q4ML, ML4Q, QCompiler... dazzled, Closing the Gap between Quantum Algorithms and Machines with Hardware-Software Co-Design
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Sim2Real Runtime Engine, for e.g. MinDOJO, autonomous driving?[X], nature of simulation: massive data, exploration cost, distributed traing <-> real.
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Carbon-aware DNN Compiler
- EDEN: Enabling energy-efficient, high-performance deep neural network inference using approximate DRAM by Koppula, Skanda, et al., MICRO 2019
- Carbon Explorer: A Holistic Framework for Designing Carbon Aware Datacenters by Acun, Bilge, et al., ASPLOS 2023
- octoml
- lamppost, energy = cost, "However, AI inference at such a massive scale is very expensive."
- Zeus
The OctoML Platform has always provided automation for exploring multiple model acceleration techniques. Via our new TVM-ONNX Runtime integration,
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Duet类似的dual device inference的nn compiler+runtime，异构子图优化，根据不同设备的并行性能优化。
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Diffusion model Survey Diffusion models: A comprehensive survey of methods and applications
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Crypto | Privacy | Security + Accelerator
- CryptGPU
- PolyMPCNet
- Crypten
- Cheetah
- On-device AI
- EfficientFormer: Vision Transformers at MobileNet Speed
- FlexiBERT: Are Current Transformer Architectures too Homogeneous and Rigid?
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zeroth order optimization (blackboxML)
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Unified abstarctions for IoT datastream.
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mlir for heter-device ml-flow (dnn & non-dnn operators & flow)
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tile ir => mixed-tile ir? cross-domain/modality ir? Pain point: multi-layer IR redundant code opt. iree support vulkan-spirv，for mobile gpu and cpu => compiler support for data flow in e2e auto vehicle
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LLM running with CNN and DNN, co-running transformer and CNN.
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大模型更强的表征能力赋给在线小模型。
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NPU running LLM, energy problem.
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llm token的稀疏性和input token的动态性使distributed inference不是所有通信都是必要的。
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machine unlearning ood
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样本端不愿意给label，都从云走的话太慢，以及云负载过大。
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未知任务识别放edge，未知任务识别在云上？
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有多少edge数据放在边缘侧可以finetune出比较好的垂直大模型？
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Simulator for edge？
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大模型compiler for edge,迁移性
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finetuning edge llm + compiler
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rTile, rGraph, 重新定义基本单元，不要以op为单位，see as dataflow。load-compute-store。大模型on edge as dynamic nn。
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Develop compiler strategies that can efficiently distribute model computations between edge and server GPUs, considering factors such as network latency, communication overhead, and load balancing.
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To facilitate this mapping, WELDER provides an abstracted accelerator device with hierarchical memory layers.
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Tensor 版本的imagebind, meta-transformer. Tuned records of same op/graphs (objects) on different hardwares (modality). Goal: unify hardware intrinsics, feature: cost model <-> svm对image到现在的encoder
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Explore Data Placement Algorithm for Balanced Recovery Load Distribution
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zpoline: a system call hook mechanism based on binary rewriting
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tensorir,code embedding, llm
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decompiling, executables to ir to another device e2e, nvidia tx2 的compiled模型，一键迁移到另一个上。