v0.30.0rc1: [Bugfix] Isolate supplemental FlashInfer BF16 autotuning (#57285)
Signed-off-by: jiahanc 173873397+jiahanc@users.noreply.github.com Co-authored-by: OpenAI Codex codex@openai.com
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1微软发布新版Copilot超级应用：整合聊天、编程与智能体能力84 热度 ⌁2Anthropic 与 Akamai 达成 116 亿美元云算力协议，年内算力支出承诺已超 5000 亿美元81 热度 ⌁3马斯克披露AI算力布局：Colossus集群拟部署超百万张英伟达GB300芯片80 热度 ⌁4谷歌启动Project Suncatcher：计划下周开展首个太空轨道数据中心测试80 热度 ⌁5微软正式推出新版 Copilot“超级应用”，整合聊天、代码与智能体能力78 热度 ⌁9月17日2026-09-17
Helping bring the world’s first large-scale, near-zero emissions steel plant online
Video opens with archival footage of smoky, coal-fired steel factories, then transitions to clean, modern exterior shots of Stegra's new facility and a clear digital animation showing how green hydrogen replaces coal to produce near-zero emission steel.
proto-v0.3.0
Release vllm-proto 0.3.0
v0.34.2-rc1: mlxrunner: lay out model by contract, checkpoint and construction
model is one package with three jobs: the contract between the runner and the architectures, the opened checkpoint, and building nn layers from checkpoint tensors. Its files did not say which was which. base.go carried the folded package's name over the interfaces and the registry, root.go held the safetensors header scan next to Root, and quant.go mixed the nvfp4 global-scale helpers with quant parameter resolution. base.go becomes model.go, named for what it holds. root.go keeps Root and Open; TensorQuantInfo and the header scan join quant.go, so everything the checkpoint says about quantization is read and resolved in one file. The global-
Translating CUDA Tile Operations from Python to Rust Using Agentic AI
cuTile Rust (cutile-rs) is a tile-based system for safe, idiomatic GPU kernel authoring in the Rust programming language. Extending the Rust ownership model to...
9月16日2026-09-16
NVIDIA Vera Rubin NVL72 Delivers Leading Performance in MLPerf Inference v6.1 Debut
System performance, efficient infrastructure scaling and continuous software optimization are key levers that determine AI inference economics. Higher system performance means more tokens generated, resulting in higher revenue. Efficient scaling means throughput grows proportionally as hardware gets added, requiring fewer resources to serve users at scale. Continuous optimization means generating more value from infrastructure investments. […]
Emerald AI, Google and NVIDIA Launch Alliance to Advance Flexible AI Data Centers
AI factories are the infrastructure of the intelligence era. Scaling them responsibly will depend as much on innovation across the grid as inside the data center. Today, Emerald AI, Google and NVIDIA announced the launch of the AI Energy Management Alliance (AEMA), a first-of-its-kind coalition advancing data centers that can dynamically manage their electricity use […]
Why Public Internet Routing Is Breaking Enterprise AI Performance
AI success isn’t just about hardware and models. Where organizations host workloads matters, as does the connectivity across those distributed workloads. When enterprises place…
proto-v0.2.0: vllm-proto 0.2.0
Validated by PR #56538 CI at fa2a26f .
EcoStruxure™ ArcFM: Turning geospatial intelligence into operational reality for modern gas utilities
As regulatory requirements continue to evolve, gas distribution operators face growing pressure to demonstrate network safety and reliability. They must also show strong environmental performance across their operations. Requirements include Distribution Integrity Management Program (DIMP) compliance and pipeline replacement initiatives. Utilities are also working to... The post EcoStruxure™ ArcFM: Turning geospatial intelligence into operational reality for modern gas utilities appeared first on Schneider Electric Blog .
How state policies change cooling decisions across India’s data centre hubs
Author: Sumati Sahgal, VP, Data Centre & Secure Power A data centre operator planning capacity in Mumbai cannot assume the same cooling economics will apply in Chennai, Hyderabad, Bengaluru, or Noida. India’s data centre incentives are largely set at the state level, where electricity concessions... The post How state policies change cooling decisions across India’s data centre hubs appeared first on Schneider Electric Blog .
Kubernetes v1.37: Pod-Level Resource Managers graduated to Beta
With the release of Kubernetes v1.37, the Pod-Level Resource Managers feature has graduated to Beta status (disabled by default)! First introduced as an Alpha feature in Kubernetes v1.36 , this enhancement builds on Pod-Level Resources by equipping Kubelet's Topology Manager, CPU Manager, and Memory Manager to use Pod-level resource declarations ( .spec.resources ) directly when making hardware placement decisions. Bringing pod-level resources to node managers Before this feature, obtaining exclusive NUMA-aligned CPU cores or memory for latency-critical applications forced cluster operators into an all-or-nothing choice: assign integer resour
From Megawatts to Tokens: How NVIDIA Maximizes AI Factory Production
On a sweltering August evening in Silicon Valley, as the sun dropped and air conditioning loads spiked, Silicon Valley Power sent a signal to an AI factory to adjust its power consumption. Varun Sivaram was watching on Zoom with about forty others — his team at Emerald AI in their San Francisco conference room, engineers […]
AI Infra Summit: NVIDIA Vera Rubin and DSX Platform Advancements Showcase Energy Efficiencies of Optimizing Tokens Per Watt for AI Factories
Ian Buck, vice president of hyperscale and high-performance computing at NVIDIA, Tuesday spoke on AI factory efficiency at the AI Infra Summit, the Santa Clara Convention Center event that has morphed into a Coachella of infrastructure tech. Before a packed audience — with more than 8,000 attendees this year, up from 3,500 last year — […]
How NVIDIA Groq 3 LPX Deterministic Execution Drives Power-Efficient High-Interactivity Inference on NVIDIA Vera Rubin
Power is a defining constraint for AI factories. As AI workloads demand a full compute platform to serve them, each component of that platform must maximize...
How NVIDIA NVLink 6 Delivers Multi-Layer Resiliency for AI Factories
For operators of large-scale AI factories, maximizing continuous output is essential for productivity. In massive-scale AI training, every GPU in the cluster...
9月15日2026-09-15
Scaling Federated Learning Across Docker, Kubernetes, and Slurm with NVIDIA FLARE
Federated learning (FL) projects often begin with a straightforward setup: one server, a few clients, and one dataset at each site. As those projects grow, the...
Optimizing conveyor operations through smart technology solutions
Introduction to intelligent conveyor control The TeSys™ Island load management and energy monitoring system represents a cutting-edge solution for modern conveyor operations, addressing critical needs such as real-time monitoring, fault differentiation, and operator safety. By leveraging embedded functionalities, this technology minimizes wiring and simplifies system... The post Optimizing conveyor operations through smart technology solutions appeared first on Schneider Electric Blog .
3 Use Cases Showing Digital Sovereignty in Action
Digital sovereignty is top of mind for many business leaders, but exactly what that entails will look different for each leader and each organization. For…
Why finance organizations need AI-tolerant UPSs for resilient AI infrastructure
Finance organizations are rapidly deploying AI workloads to support fraud detection, risk modeling, customer service, and other high-performance applications. As GPU-based AI infrastructure expands, many IT teams are discovering that traditional power architectures were not designed to handle the rapid load fluctuations these workloads create.... The post Why finance organizations need AI-tolerant UPSs for resilient AI infrastructure appeared first on Schneider Electric Blog .
How we trained the fastest DSpark for Kimi-K3 using GB300 NVL72
How Speculators and Mooncake enabled multi-node DSpark training for Kimi K3.
vLLM x Novita AI: Chord, Faster INT4 MoE for Kimi K2.x. Up to 1.3x on H200, 2.15x on Untuned B300
Novita AI has open-sourced Chord, a high-performance W4A16 MoE CUDA kernel for Kimi K2.x serving shapes, with a Humming-compatible indexed path and grouped SM90
9月14日2026-09-14
We’re exploring a potential data center in Lea County, New Mexico.
Google is exploring a new data center project in Lea County, New Mexico. While discussions are ongoing, we recognize residents are asking questions about data center dev…
vime × RL-Kernel × AMD: Bitwise Train–Rollout Consistency on ROCm
vime and RL-Kernel align selected-token logprobs bit for bit across Megatron training and vLLM rollout on AMD Instinct MI300X, with zero mismatches across 200 G
9月13日2026-09-13
v0.29.1rc0
[watermarking] Dual-key gumbel-max watermarking for speculative decod…
Kimi K3 Performance Optimizations in vLLM: The Road to 2.8× Throughput
Kimi K3 serving optimizations across scheduling, KDA prefix caching, ReplaySSM state recovery, PD disaggregation and state offload, parallelism, MoE, and GPU ke
9月11日2026-09-11
More Choice Shouldn’t Mean More Complexity: The Case for Any-to-Any Connectivity
Every new cloud, AI provider or partner that an enterprise chooses to work with could mean another connection to design, provision and manage. As…
1 new IEC standard for semiconductor circuit-breakers
Until now, circuit-breakers have relied on the electrical arc generated by the separation ofmetallic contacts to interrupt both normal and fault currents. This principle, introducedover a century ago, has remained the foundation of conventional circuit-breakertechnology. Transistors such as MOSFETs* or IGBTs** have been widely used... The post 1 new IEC standard for semiconductor circuit-breakers appeared first on Schneider Electric Blog .
Rapidly scaling online storage to serve over 1 billion ChatGPT users
Learn how OpenAI evolved Habitat from a Python library into a globally distributed storage platform serving 1 billion ChatGPT users and 22M requests per second.
proto-v0.1.0
vllm-proto 0.1.0