I gave a talk at the Future Network Development Conference (FNDC) in Nanjing on August 20th, 2025. The title of the talk was Connecting AI: Inter-Networking Challenges for Distributed Machine Learn…| Dirk Kutscher
Our paper on INDS: Incremental Named Data Streaming for Real-Time Point Cloud Video has been accepted at ACM Multimedia 2025. Abstract: Real-time streaming of point cloud video – characterized by high data volumes and extreme sensitivity to packet loss – presents significant challenges under dynamic network conditions. Traditional connection-oriented protocols such as TCP/IP incur substantial […]| Dirk Kutscher
Generative AI systems are approaching a scalability limit in their development. Due to power density issues, it will soon become infeasible to train large language models with an increasing number of parameters in a single datacenter. While the industry is actively pursuing an effort to scale up AI systems, it becomes necessary to explore the […]| Dirk Kutscher
Our paper on AdaptQNet: Optimizing Quantized DNN on Microcontrollers via Adaptive Heterogeneous Processing Unit Utilization has been accepted at ACM MobiCom-2025. Abstract There is a growing trend …| Dirk Kutscher
I gave a talk about the Internet Research Task Force (IRTF) at an IETF Standards Culture and Process Deep-Dive Training that took place in Beijing on May 8th, 2025. The training was hosted by the C…| Dirk Kutscher
Our paper on NetSenseML: Network-Adaptive Compression for Efficient Distributed Machine Learning has been accepted at the 31st International European on Parallel and Distributed Computing (Euro-Par-2025). Abstract: Training large-scale distributed machine learning models imposes considerable demands on network infrastructure, often resulting in sudden traffic spikes that lead to congestion, increased latency, and reduced throughput, which would […]| Dirk Kutscher
Our paper on Trochilus, titled Learning-Enhanced High-Throughput Pattern Matching Based on Programmable Data Plane has been accepted at USENIX ATC-2025. This is joint work with Qing LI's group at Peng Cheng Lab, and the first author is Guanglin DUAN. Abstract: Pattern matching is critical in various network security applications. However, existing pattern matching solutions struggle […]| Dirk Kutscher
Our paper on Rethinking Dynamic Networks and Heterogeneous Computing with Automatic Parallelization has been accepted by the 9th Asia-Pacific Workshop on Networking (APNET'25). Abstract: Hybrid parallelism techniques are crucial for the efficient training of large language models (LLMs). However, these techniques often introduce differentiated computational and communication tasks across nodes. Existing automatic parallel planning frameworks […]| Dirk Kutscher
Our paper on ViFusion: In-Network Tensor Fusion for Scalable Video Feature Indexing has been accepted at the ACM International Conference on Multimedia Retrieval 2025 (CCF-B). Abstract: Large-scale…| Dirk Kutscher
The IETF has recently published an interview with me on the IETF Blog.| Dirk Kutscher
