![]() ![]() ![]() TrueNorth is IBM's Neuromorphic CMOS ASIC developed in conjunction with the DARPA SyNAPSE program. ![]() The 7 nm microprocessor is engineered to meet the demands our clients face for gaining AI-based insights from their data without compromising response time for high volume transactional workloads. IBM Telum Processor: the next-gen microprocessor for IBM Z and IBM LinuxONE It’s our first complete system-on-chip designed to run and train deep learning models faster and more efficiently than a general-purpose CPU. Meet the IBM Artificial Intelligence Unit According to NVIDIA, the chip is being designed specifically for large-scale neural network workloads, and is expected to become available in NVIDIA products in 2023. Dubbed Grace – after Grace Hopper, the computer programming pioneer and US Navy rear admiral – the CPU is NVIDIA’s latest stab at more fully vertically integrating their hardware stack by being able to offer a high-performance CPU alongside their regular GPU wares. Kicking off another busy Spring GPU Technology Conference for NVIDIA, this morning the graphics and accelerator designer is announcing that they are going to once again design their own Arm-based CPU/SoC. NVIDIA Unveils Grace: A High-Performance Arm Server CPU For Use In Big AI Systems This post gives you a look inside the new H100 GPU and describes important new features of NVIDIA Hopper architecture GPUs. Today during the 2022 NVIDIA GTC Keynote address, NVIDIA CEO Jensen Huang introduced the new NVIDIA H100 Tensor Core GPU based on the new NVIDIA Hopper GPU architecture. Tens of Thousands of NVIDIA GPUs, NVIDIA Quantum-2 InfiniBand and Full Stack of NVIDIA AI Software Coming to Azure NVIDIA, Microsoft and Global Enterprises to Use Platform for Rapid, Cost-Effective AI Development and Deployment NVIDIA Teams With Microsoft to Build Massive Cloud AI Computer Add news of Synopsys DesignWare ARC NPX6 NPU IP.Add startup Modular AI in AI compiler section.Add news of Tachyum Prodigy Universal Processor.Add link to Latest MLPerf Results from MLCommons. ![]()
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