…Today’s MoE models impose higher and more complex requirements for parallel strategies, low-precision computing, and dynamic resource scheduling. They also need optimization to maximize the potential of next-generation hardware…
…This includes GPU telemetry, kernel logs, hardware events, PCIe state, firmware information, and crash diagnostics. The bundle is produced as an artifact on-device; the tool returns a pointer through stdout so…
…This includes configuring I/Os, clock settings, fan control, power profiles, or any other module for a specific hardware design. Tasks that previously required weeks of manual effort can be handled by…
…Confidential Containers (CoCo) operationalize it for Kubernetes. CoCo enables Kubernetes pods to run inside hardware-backed TEEs without requiring application rewrites. Instead of sharing the host kernel, each pod is transparently wrapped…
…Defining the kernel interface In cuTile, the @ct.kernel decorator marks a Python function as a GPU kernel. We pass compile-time constants using ct.Constant[T] type annotations: import math import…
…Due to the requirement for ultra-low-latency communication for intermediate activations between stages, these transfers are typically initiated by the GPU through optimized kernels, referred to as device side APIs for…
…This post explains a technique known as Skip Softmax, a hardware-friendly, drop-in sparse attention method that accelerates inference without any retraining. Read on to learn how Skip Softmax delivers up…
…CUTLASS Modular C++ templates and Python DSLs for building high-performance kernels targeting NVIDIA Tensor Cores. FlashInfer GPU-accelerated kernel library, accessible via Python API for inference, optimizing attention, MoEs, GEMMs, comms…
…Live data processing—to promptly send alerts to telescopes around the world and steer observation decisions—requires accelerated computing. These steps require advanced image calibration, basis constructions, convolutions, subpixel differencing, pattern extraction…
…The software stacks are also aligned—kernel, user space, and AI libraries share the same versions—delivering a consistent experience across Jetson and IGX. For teams with deeper customization requirements, NVIDIA is…