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Explore HPC/HTC landscape in cloud-native environments, covering solutions, deployments, workload migration, resource management, and tools for high-performance computing.
Explore advanced Kubernetes networking for AI and HPC workloads, focusing on multi-interface support, Multus CNI, and the new Multi-NIC CNI project for improved performance and scalability in large-scale GPU clusters.
Explore NUMA-aware scheduling in Kubernetes for HPC workloads, addressing challenges, solutions, and future developments in resource orchestration and performance optimization.
Explore Volcano, a cloud native batch system for AI, BigData, and HPC. Learn about its features, use cases, and integration with computing ecosystems to accelerate workloads and improve cluster utilization.
Explore KubeFlux, a Kubernetes plugin integrating HPC scheduling capabilities. Learn about its performance benefits and potential for enhancing cloud-based high-performance computing workloads.
Explore HPC and AI-enabled real-time coherent X-ray diffraction imaging, revolutionizing materials characterization with advanced light sources, multi-modal techniques, and innovative data processing methodologies.
Explore TACC, a unified cloud-native infrastructure for AI and HPC, bridging K8S and Slurm advantages. Learn about seamless UI, multi-tenant resource management, and robust distributed infrastructure.
Explore coordinated checkpointing for distributed HPC applications across multiple Pods and nodes, including new CRIU mechanisms, Kubelet Checkpoint API, and potential Kubernetes scheduler extensions.
Explore InterLink, an open-source Virtual-Kubelet extension enabling seamless access to external hardware-accelerated machines through Kubernetes APIs, revolutionizing scientific computing workflows.
Explore mixed precision algorithms in HPC, focusing on convergence properties and performance considerations for modern hardware implementations of floating-point arithmetic.
Explore Julia's potential in HPC, combining scientific ecosystem with high performance. Gain insights on its strengths, limitations, and notable international projects from an experienced user.
Explore recent LLVM efforts for HPC: portable CUDA, debugging at scale, GPU execution of legacy codes, automatic differentiation, ML in compilers, and static information impact.
Explore the capabilities and differences of various HPC GPUs, comparing NVIDIA models, examining competitors, and understanding new developments like APUs.
Explore LLVM's impact on HPC, covering portable CUDA, debugging at scale, GPU execution of legacy code, and ML in compilers. Learn about efforts to enhance performance, tooling, and development in HPC.
Dive into advanced SmartNIC implementation strategies for optimizing high-performance computing and data center operations, covering deployment techniques and performance optimization.
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