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The Deepview Corp. X400 Camera is a high-performance fully integrated vision system with a 1.2MP CMOS sensor capable of either color or monochrome imaging. It integrates a NVIDIA Volta GPU, a 6-core CPU, and 8GB of DDR4 RAM, enabling advanced deep learning algorithms for real-time image analysis and pass/fail inspections. The system offers 1TB of storage and supports a cycle time of 150ms. The camera integrates seamlessly with PLC EtherNet/IP systems and is accessible via a web app and browser interface. www.deepviewai.com #embeddedsystems #ai #inspection #computervision

What if we could revolutionize AI training by using NVMe as a third-tier of “slow” memory to run training jobs on single GPU systems that used to require multiple GPU systems? At #GTC24, Micron, in collaboration with NVIDIA and Dell Technologies, demonstrated how our Gen5 SSD tech demo is perfectly suited for AI model offloading. We utilized the open-source BaM/GIDS software stack on a Dell PowerEdge R7625, equipped with an NVIDIA H100 80GB PCIe GPU (Gen5). The results were nothing short of astounding! Explore how Gen5 storage truly excels in the realm of AI with this new blog from Ryan Meredith, Micron director of storage solutions architecture: https://bit.ly/4a0VDvD

Hello AI community! I'm testing a new hardware setup for LLM inference and fine-tuning. I'm looking for suggestions on the best tests to gauge the efficiency and affordability of this hardware. Specifically, I'll be comparing the NVIDIA H100 and AMD MI300X GPUs to evaluate their efficiency and affordability for LLM inference and fine-tuning tasks. Some key things I'm hoping to evaluate are: - Inference latency and throughput for different model sizes - Memory usage during fine-tuning on various datasets - Power consumption and thermal characteristics - Assessing the hardware cost and total cost of ownership for deploying LLM workloads on these GPUs If you have experience benchmarking LLM hardware, I'd appreciate any advice on the most important metrics to measure. Please share your thoughts in the comments. #llm #hardware #inference #nvidia #amd

I've been playing with matrix multiplication on GPUs, using a Hilbert curve to improve L2 cache utilization, and seeing if I can get non-embarrassing performance out of it. Seems this approach can outperform Nvidia's cuBLAS for matrix sizes of 16384x16384 and above. Blog post here with open source code on GitHub for anyone who'd like to mess with it too. #gpu #cuda #cplusplus https://lnkd.in/e4QvmSVR

𝗜𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝗶𝗻𝗴 𝘁𝗵𝗲 𝗫𝟮𝟬𝟬𝟬 𝗠𝘂𝗹𝘁𝗶𝗖𝗮𝗺 𝗦𝗲𝗿𝘃𝗲𝗿 We’re proud to present the X2000 MultiCam Server, a high-performance industrial PC designed for advanced neural network image detection. Powered by an NVIDIA GPU and 32GB DDR5 RAM, it delivers real-time image analysis across multiple camera setups, making it ideal for industrial inspection and monitoring. 𝗞𝗲𝘆 𝗙𝗲𝗮𝘁𝘂𝗿𝗲𝘀: • 𝗔𝗜-𝗣𝗼𝘄𝗲𝗿𝗲𝗱 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴 Embedded NVIDIA™ GPU and CPU for real-time image analysis. • 𝗕𝘂𝗶𝗹𝘁-𝗶𝗻 𝗗𝗲𝗲𝗽 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗧𝗿𝗮𝗶𝗻𝗶𝗻𝗴 𝗔𝗽𝗽 Remotely connect to, and train with, the X2000 MultiCam Server. • 𝗜𝗻𝗱𝘂𝘀𝘁𝗿𝗶𝗮𝗹-𝗚𝗿𝗮𝗱𝗲 𝗗𝗲𝘀𝗶𝗴𝗻 Fanless, rugged construction ideal for industrial environments. • 𝗟𝗮𝗿𝗴𝗲 𝗦𝘁𝗼𝗿𝗮𝗴𝗲 𝗖𝗮𝗽𝗮𝗰𝗶𝘁𝘆 4TB storage for extensive image history. • 𝗦𝗶𝗺𝗽𝗹𝗲 𝗖𝗼𝗻𝗻𝗲𝗰𝘁𝗶𝘃𝗶𝘁𝘆 Features GigE, SFP+ and USB camera integration. 𝗪𝗮𝗻𝘁 𝘁𝗼 𝗹𝗲𝗮𝗿𝗻 𝗺𝗼𝗿𝗲? 𝗚𝗲𝘁 𝗶𝗻 𝘁𝗼𝘂𝗰𝗵 𝘄𝗶𝘁𝗵 𝘂𝘀 𝘁𝗼𝗱𝗮𝘆! #MachineVision #IndustrialAutomation #Technology #Innovation #X2000 #DeepviewCorp

Check out the latest issue of The Parallel Universe for articles on how far #oneAPI has come, how Intel’s new built-in AI acceleration engines are ushering in a new era of accelerated #AI on Intel CPUs, and more. #IAmIntel https://bit.ly/3WXH33C

To kick off #CES2025, NVIDIA Project DIGITS was announced, a Linux-based system featuring 20 Arm-powered CPU cores. Christopher Bergey explores how the Arm-based technology in the GB10 Superchip, used in Project DIGITS, helps makes it possible for every AI developer to have a high performance AI system on their desk.

Exploring CPU Optimization on Jetson Orin Nano with OpenVINO 🚀 In our recent study with the Jetson Orin Nano, we explored how Intel’s OpenVINO toolkit can be leveraged for CPU optimization alongside traditional GPU acceleration with CUDA, creating a flexible, balanced approach. This setup incorporates two models: Person Detection – running on OpenVINO with a 2.096x speedup over standard CPU inference. Pose Estimation – leveraging the GPU for efficient, high-speed processing. A key element here is the use of OpenCV as a unified dependency, enabling seamless inference across both #OpenVINO and CUDA. By using OpenCV, we not only simplify the framework but also make it easier to optimize performance across diverse processing units. Why rely on GPU alone when we can efficiently balance the load across CPU and GPU? By balancing the load across GPU and CPU, we can avoid over-relying on any single resource, creating a more optimized and flexible solution. Future work To enhance performance further: 1. Utilizing OpenCL with T-API to offload preprocess and postprocess tasks for greater efficiency. 2. Integrating TensorRT to maximize acceleration across TPU, CPU, and GPU bringing the best of all processing units together to unlock the full potential of our hardware. Ayşe Vildan Nurdağ Şeyma Kandemir Erdem Kaya Kutay Kılıç #HardwareAcceleration #OpenVINO #JetsonOrinNano #CPUOptimization #GPU #CPU #AI #MachineLearning #OpenCV #EdgeComputing #ComputerVision #ObjectDetection #RealTime

Introducing the FT65TB8050 #AI Server, engineered for demanding AI and high-performance computing (#HPC) tasks.   With support for #AMD #Turin CPUs and multiple GPUs, it’s designed to handle AI training, inference, and deep learning workloads effortlessly.   Equipped with DDR5 6000 memory, PCIe 5.0 slots, and hot-swap NVMe storage, it ensures seamless data processing and fast access for complex computational tasks. Whether running advanced simulations, analyzing massive datasets, or optimizing performance-intensive applications, the FT65TB8050 delivers the power and flexibility you need to drive innovation.   Product Information👉https://pse.is/FT65TB8050   #AIPowered #ServerSolutions #Innovation #TechSolutions #FutureOfIT #EnterpriseTech #MiTACcomputing

As #AI-powered workflows become more sophisticated, more falls on the shoulders of #DataScientists to put that #data to work. 🚧 And they need GPUs and CPUs that are going to keep pace. Cue the Lenovo ThinkStation P8, powered by AMD and NVIDIA Design and Visualization. Together, we're delivering agility, efficiency and affordability for the AI professionals of today and tomorrow. 💡 https://lnv.gy/4741LlX