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All CFPs on WikiCFP | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Present CFP : 2024 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
VHPC'24: August 26th-27th, Madrid, Spain, co-located with Euro-Par 2024. Papers due: Jun 7th.
The Workshop on Virtualization in High-Performance Cloud Computing (VHPC) aims to bring together researchers and industrial practitioners facing the challenges posed by virtualization in HPC/Cloud scenarios in order to foster discussion, collaboration, mutual exchange of knowledge and experience, enabling research to ultimately provide novel solutions for virtualized computing systems. The workshop features paper presentations, discussion sessions, and lightning talks. Accepted papers will be published in a Springer LNCS volume (indexed by Scopus and others). --- Focus Topics --- This year, we are calling the timely topic of virtualization in support of high-memory LLM training workloads including, but not limited to: -) GPU hypervisor memory virtualization: Techniques for virtualizing GPU memory to allow flexible and efficient allocation across multiple workloads, enabling higher utilization of GPU resources -) Flat CPU/GPU memory page tables/TLB: Unified virtual memory spaces and page table structures that allow both GPUs to address CPU memory mapped to accelerator global memory space -) Storage/filesystem to virtual memory mapped approaches -) Distributed memory virtualization -) Memory compression and reduction techniques: approaches for compressing model parameters, activations, and gradients to reduce memory requirements during training -) Out-of-core training algorithms -) Efficient memory allocation and management: Techniques for optimizing memory allocation, reducing fragmentation, and improving memory utilization during training -) Memory-efficient data formats and processing: Data formats and processing techniques that minimize memory overhead while maintaining training efficiency -) Benchmarking and profiling tools: Tools and methodologies for measuring, analyzing, and optimizing memory usage in LLM training workloads -) Case studies and applications: Real-world examples and applications of virtualization techniques in LLM training scenarios In addition to regular topics: -) Container Platforms (Kubernetes, Docker, Nitro/Firecracker, Singularity, Shifter, rkt, …) and Unikernel Frameworks -) Composable Lightweight Application Components and Lambda / Function-as-a-Service Paradigms -) Latency Control, Warm/Cold-start issues and Data/Container Placement in Heterogeneous HPC Virtualized Environments -) Energy-efficiency and Service Orchestration in Virtualized Cloud & HPC Infrastructures The workshop will be composed of 20 min paper presentations, each followed by 10 min discussion sessions, plus lightning talks that are limited to 5 minutes. Presentations may be accompanied by interactive demonstrations. For more information and detailed paper submission instructions, refer to the VHPC'24 webpage. --- Important Dates (AoE) --- Jun 7th, 2024: Paper submission deadline (Springer LNCS) Jun 20th, 2024: Acceptance notification Jul 1st, 2024: Camera-ready version due Aug 26th-27th, 2024: Workshop Day --- Workshop Chairs --- Michael Alexander (chair), University of Vienna, Austria Anastassios Nanos (co-chair), Nubificus Ltd., UK Tommaso Cucinotta (co-chair, Scuola Superiore Sant'Anna, Italy --- Publicity Chairs --- Remo Andreoli, Scuola Superiore Sant'Anna, Italy --- General Information --- The workshop will be held in conjuction with the International European Conference on Parallel and Distributed Computing (Euro-Par 2024), on Aug 26th-27th, 2024, in Madrid, Spain. The VHPC co-chairs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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