REVO.tech - B2B Global Electronics Marketplace的动态

Huge Cost-Savings opportunity on #Nvidia #H100 #GPU PCIe Cards this week Without Long Factory lead times! 900-21010-0300-030 HPE Spare Part Number: P54751-001 We are excited to announce that we have 740 units of the powerful?#Nvidia #H100?in stock and ready for immediate shipping! Key Features: Memory:?80GB HBM2e for handling the most demanding applications Compute Capability:?7,000+ TFLOPS of AI performance Architecture:?Nvidia Hopper, designed for next-generation AI and HPC workloads NVLink:?Supports Nvidia NVLink for high-speed GPU-to-GPU communication Efficiency:?Advanced power management for optimal performance and energy efficiency Ideal For: Artificial Intelligence & Machine Learning Data Science High-Performance Computing (HPC) Deep Learning Rendering Contact us at [email protected] if you require other electronics parts, or if you have your own electronics Excess that you would like to sell! #ampere #electronics #semiconductor #embeddedsystems #iot #semiconductors #electronicmanufacturing #processors #microcontrollers #digitalsignage #nxp #STMicroelectronics #electronicsengineering #components #electroniccomponents #infineon #microcontrollers #microcontroller #cpu #microchip #displays #monitor #kiosks #touchscreen #LCD #displaytechnology #openframe #lcddisplay #samsungdisplay #lg #philips #monitors #monitor #itad #ithardware #excessinventory #excess #excessstock #surplus #wholesalers #wholesaler #wholesale #wholesaledistribution #wholesaledistributor #gpu #ssd #nvidia #nvidiartx #Switches #GPU #DGX #Datacenter #A100 #H100 920-24387-2540-0R0 920-24387-2540-000 920-24387-2540-1R0 920-24387-2540-100 965-2G520-0100-0R0 965-2G520-0100-000 965-2G520-0101-000 965-2G520-0101-0R0 965-2G520-0131-400 965-2G520-0131-4R0 935-23087-0021-300 935-23087-0001-000 935-23087-0101-000 935-23087-0101-0R0 935-23087-0031-400 935-23087-0131-400 935-23087-0131-4R0 935-24287-0000-000 935-24287-0100-000 935-24287-0100-0R0 935-24287-0001-100 935-24287-0001-000 935-24287-0010-300 900-21010-0120-030 900-21010-0020-000 900-21010-0020-001 900-21010-0100-030 900-21010-0000-000 900-21010-0000-001 900-21010-0100-031

New Inventory Alert: #NVIDIA A100 Baseboards Available Now! We are thrilled to announce the availability of NVIDIA A100 baseboards, the industry-leading GPUs designed to accelerate AI, machine learning, and high-performance computing workloads. Available Models: NVIDIA A100 Baseboard - 48GB Quantity: 14 units ? Model Number: GPU-NVTHGX-A100-SXM4-48 ? Part Number: 935-22687-0030-200 ? Memory: 48GB HBM2 NVIDIA A100 Baseboard - 80GB Quantity: 1,400 units ? Model Number: GPU-NVTHGX-A100-SXM4-88D ? Part Number: 935-23587-0000-204 ? Memory: 80GB HBM2e Key Features: ? Unmatched Performance: The NVIDIA #A100 #baseboards are built on the latest Ampere architecture, delivering breakthrough performance for #AI, deep learning, and scientific computing. ? High Memory Bandwidth: Equipped with high-bandwidth memory (HBM2 and HBM2e) to handle large datasets and complex models with ease. ? Versatile Applications: Ideal for accelerating workloads in #datacenters, cloud services, AI research, and more. ? Scalability: Designed for multi-GPU setups, enabling scalable performance for the most demanding computational tasks. Contact us at [email protected] for more details or to place an order. If you have your own electronics excess that you would like to sell, we are here to help! 699-24612-1000-302 675-23687-0000-301 699-24612-1000-302 699-2G506-0210-330 694-22687-0030-200 699-2G506-0200-300 965-2G506-0030-000 966-2G505-0031-000 699-2G506-0200-300 699-2G506-0212-320 699-2G506-0222-QS1 699-24612-1000-301 699-24612-1000-900 935-23587-0000-200 935-23587-0000-000 675-24287-0001-EV2 #DeepLearning #HPC #H200 #GH200 #Server #Servers #HDD #NVMe #ITAD #DDR5 #DDR4 #Jetson #Transceivers #excessinventory #electronics #semiconductor #embeddedsystems #iot #semiconductors #electronicmanufacturing #processors #microcontrollers #excessstock #surplus #wholesalers #wholesaler #wholesale #gpu #nvidia #nvidiartx #Switches #GPU #DGX #A100 #H100 #itad #IThardware

New Inventory Alert: #NVIDIA #A2 Half-Length #GPUs Available Now! We are excited to announce the availability of NVIDIA A2 16GB GPUs, specifically designed for compact, high-performance computing environments. These half-length GPUs are ideal for AI inference, machine learning, and data center applications where space and power efficiency are crucial. ? Model Number: 699-2G179-0220-200 ? Memory: 16GB GDDR6 ? Architecture: Ampere ? Form Factor: Half-Length, Single-Slot ? Power Consumption: 60W TDP ? Cooling: Passive Key Features: ? Compact Design: Half-length, single-slot form factor makes the NVIDIA A2 ideal for deployment in dense server environments or edge computing devices. ? Efficient Performance: Powered by the NVIDIA Ampere architecture, this GPU offers robust performance for AI inference and machine learning workloads while maintaining a low power draw of just 60W. ? High Memory Capacity: Equipped with 16GB of GDDR6 memory, the A2 is capable of handling complex models and large datasets with ease. ? Passive Cooling: Designed with passive cooling, making it perfect for environments where airflow and space are limited. ? Versatile Applications: Suitable for use in AI inference, virtual desktops, and other compute-intensive tasks in space-constrained environments. Contact us at [email protected] for more details or to place an order. If you have your own electronics excess that you’d like to sell, we’re here to help! #AI #DeepLearning #HPC #H200 #GH200 #Server #Servers #HDD #NVMe #ITAD #DDR5 #DDR4 #Jetson #Transceivers #excessinventory #electronics #semiconductor #embeddedsystems #iot #semiconductors #electronicmanufacturing #processors #microcontrollers #excessstock #surplus #wholesalers #wholesaler #wholesale #gpu #nvidia #nvidiartx #Switches #GPU #DGX #A100 #H100 #itad #IThardware 900-2G179-0120-001 900-2G179-0120-000 900-2G179-0020-000 900-2G179-0020-001 900-2G179-0120-100 900-2G179-0120-101 900-2G179-0020-100 900-2G179-0020-101

NVIDIA A100X Converged Accelerator – 80GB Units Ready for Immediate Deployment- Cost-saving stock The NVIDIA A100X is purpose-built for data-intensive applications across AI, HPC, and deep learning, combining GPU and networking capabilities in one accelerator for maximum efficiency in data center deployments. Model: NVIDIA A100X Converged Accelerator 80GB Part Number: 900-21004-0030-000 - Memory: 80GB HBM2e memory with high bandwidth to handle large datasets efficiently - Tensor Cores: 3rd Gen Tensor Cores supporting mixed-precision (FP16, FP32, INT8) for enhanced AI model training and inference - CUDA Cores: Thousands of CUDA cores for parallel processing, accelerating compute-heavy tasks - Networking: Built-in high-speed networking for multi-node scaling and reduced data movement latency - NVLink: NVLink support for interconnectivity between multiple GPUs in a system - Form Factor: PCIe Gen4 compatible, enabling faster data transfer across various setups - Power Efficiency: Optimized TDP for balanced power consumption and performance If your company has A100X or similar GPUs that it may be interested in selling, please reach out—we’re actively looking to source additional stock. Contact us at [email protected] for more details or to place an order. If you have your own electronics excess that you would like to sell, we are here to help! #EdgeComputing #DeepLearning #HPC #H200 #GH200 #Server #Servers #HDD #NVMe #ITAD #DDR4 #Jetson #Transceivers #electronics #semiconductor #embeddedsystems #iot #semiconductors #electronicmanufacturing #processors. #microcontrollers #wholesalers #nvidia #nvidiartx #Switches #GPU #DGX #A100 #H100 #IThardware #Datacenter #Datacentre #AIDATACENTER #GB200 #GH200 #Blackwell #L40S #RTX4090 #AI #CPU

The use of AI is rapidly increasing across various industries, and running AI models requires powerful GPUs. But here is the thing, GPUs require a lot of power. For instance, Nvidia’s H100 GPU, a flagship AI accelerator, consumes up to 700W per chip. By 2026, AI power demand is projected to surge by over 550%, reaching 52 TWh annually. On top of that, electric vehicles are growing fast in India and globally, and this trend is set to grow significantly over the next 10 years. With all this happening, one thing is clear, power demand is going to skyrocket. That's why I am super bullish on power stocks, especially companies focused on renewable and innovative energy solutions. What are your thoughts on this?

?? Meet Sohu: The Fastest AI Chip of All Time ?? Imagine processing over 500,000 tokens per second with the Llama 70B model. Sohu makes it possible, offering unprecedented capabilities that surpass traditional GPUs. One 8xSohu server can replace 160 H100s. ?? Specialization at Its Best Sohu is the first specialized chip (ASIC) designed for transformer models, delivering unmatched performance. While it can’t run CNNs, LSTMs, or other AI models, its focus on transformers gives it a significant edge. Why Specialized Chips are the Future: ?? Sohu is >10x faster and cheaper than NVIDIA’s next-gen Blackwell (B200) GPUs. ?? One Sohu server processes 500,000 Llama 70B tokens per second—20x more than an H100 server, and 10x more than a B200 server. ?? Benchmarked in FP8 without sparsity, using 8x model parallelism with 2048 input/128 output lengths. Figures are from TensorRT-LLM 0.10.08 (latest version), and 8xB200 figures are estimated. ?? The Limitations of GPUs GPUs are becoming larger, not better. Compute density has only improved by ~15% over the past four years. Upcoming GPUs (like NVIDIA B200, AMD MI300X, Intel Gaudi 3, AWS Trainium2) are merely doubling chips to boost performance. ?? With Moore’s law slowing, specialization is the path forward. Economics of Scale: ?? AI models now cost $1B+ to train and generate $10B+ in inference. At this scale, even a 1% improvement can justify a $50-100M custom chip project. ?? ASICs are 10-100x faster than GPUs. This was evident with bitcoin miners in 2014, and it’s now transforming AI. The Hardware Lottery: Transformers dominate because they run fastest and cheapest on current hardware. AI labs have optimized transformers extensively, making them the most efficient choice for large-scale models. The Future: As Sohu and other ASICs enter the market, a shift is inevitable. Future transformer killers will need to outperform transformers on GPUs and custom chips alike. When they do, we’ll be ready to build the next generation of ASICs. ?? Get Ready for the Sohu Revolution. #Innovation #ArtificialIntelligence #Chip

?????????? ???? ???? ?????????????? ???? -> ?????? NVIDIA ???????? TrueFoundry ???? ???????????? ?????????????? ?????? ???????????? LLM, Finetuning, RAG – we're all drowning in AI jargon. But I really promise, this is one of the coolest applications of these capabilities you’ll come across. In a world where GPUs are as valuable as gold (and yes, they’re actually shipped to data centers in armored vehicles), NVIDIA has rolled out a very innovative solution to unlock their GPUs' full potential. Imagine AI agents working nonstop to optimize GPU clusters - enhancing performance and reducing wait times for everyone who needs GPUs. NVIDIA has built a multi-agent AI system to optimize GPU cluster utilization by processing real-time telemetry data. TrueFoundry served as the orchestration layer, enabling seamless multi-cloud management and LLM agent deployment to enhance NVIDIA’s GPU performance. ?? K?e?y? ?H?i?g?h?l?i?g?h?t?s?: ?? Multi-agent LLM system automates cluster optimization ?? Real-time processing of GPU telemetry data ?? Potential for multi-hundred-million dollar impact #ai #gpu #gpus #llm #llms #nvidia #datacenters #artificialintelligence

Exclusive?Cost-Savings opportunity on Nvidia Jetson Xavier NX Modules Available Now! Below Market price & Without Lead Time! We are excited to offer 200 units of the Nvidia Jetson Xavier NX modules, designed to bring exceptional AI performance to embedded systems and edge computing applications. These modules provide unmatched power and efficiency for AI, machine learning, and computer vision projects. Model: Nvidia Jetson Xavier NX (900-83668-0000-000) Quantity: 200 units - AI Performance: Up to 21 TOPS (Tera Operations Per Second) for AI inference tasks. - CPU: 6-core NVIDIA Carmel ARMv8.2 64-bit processor, operating at 1.4 GHz to 2.3 GHz. - GPU: 384-core NVIDIA Volta GPU with 48 Tensor Cores. - Memory: 8GB LPDDR4x memory, offering a bandwidth of 51.2GB/s. - Storage: 16GB eMMC (expandable via microSD) - Video Encoding/Decoding: Supports 4K 60fps video encoding and decoding. - Power Consumption: Configurable between 10W and 15W, making it highly efficient for power-constrained devices. - Networking: Supports Gigabit Ethernet and wireless connections via an add-on module. Contact us at [email protected] for more details or to place an order. If you have your own electronics excess that you would like to sell, we are here to help! #DeepLearning #HPC #H200 #GH200 #Server #Servers #HDD #NVMe #ITAD #DDR5 #DDR4 #Jetson #Transceivers #excessinventory #electronics #semiconductor #embeddedsystems #iot #semiconductors #electronicmanufacturing #processors #microcontrollers #excessstock #surplus #wholesalers #wholesaler #wholesale #gpu #nvidia #nvidiartx #Switches #GPU #DGX #A100 #H100 #itad #IThardware

The entrance of NVIDIA in the computing market through AI At the server level, it has allowed the company to reach historical highs, both in sales and in developed technologies, since they have managed to become the company with the highest value in the world thanks to the development of components related to artificial intelligence. But obviously there are always ways to improve the power that the hardware is capable of achieving, and this time they have created a superchip which combines multiple B200 GPUs along with a pair of Grace CPUs to deliver the highest possible data center performance. Data centers have high-performance systems that allow a large amount of information to be processed simultaneously, something that is increasingly increasing due to the development of new technologies that require computing power much higher than what we could see ago. only four years. For this reason, those companies that have specialized hardware for a technology that allows data processing to be faster and easier are the ones that currently lead the market, being the main representative of this case. NVIDIA thanks to your chips created for AI. NVIDIA’s new AI processor has four B200 GPUs and two Grace CPUs fused together There are more and more advances that we see in the computing sector that allow us to manage in a much more efficient way the large amount of data that is generated daily on servers, and in this case the arrival of artificial intelligence has managed to improve this aspect a lot. Now NVIDIA has presented a new chip that will allow for even higher performance, as it combines several of its most important technologies to surpass the power offered by the GB200 Grace Blackwell, which already incorporated two high-performance GPUs, but the new one includes the double. And it is that he GB200 Grace Blackwell NVL4 Superchip It is a variant that incorporates a total of four Blackwell B200 GPUs connected together via NVLink, along with two ARM-based Grace CPUs, all combined on one motherboard (which is why we don’t know why the company calls it a “superchip” ). The new GB200 NVL4 It manages to offer 2.2 times higher performance in simulation, 1.8 times higher in training and 1.8 times higher in inference compared to its predecessor, the GH200 NVL4 Grace Hopper Superchip. In addition to this, the company has also introduced a new dual-slot graphics card, the NVL H200intended for data centers that has air cooling and PCIe 5.0 connectivity, which should allow reaching 128 GB/s. This model is specifically designed to present a continuous airflow that circulates from right to left, without blower fans, in addition to being optimized for rack mounting solutions. Its performance will be slightly lower than that offered by the H200 GPUbut the company assures that the NVL H200 is far superior to the one it intends to replace, the NVL H100 since it has 1.5 times more memory capacity and 1.2 times more memory bandwidth.

Is This The Next Big Thing? Etched is set to redefine AI hardware with Sohu, the world's first ASIC chip designed specifically for transformers. This revolutionary product delivers exceptional performance and efficiency that surpasses even the latest GPUs. Sohu boasts a remarkable throughput of over 500,000 tokens per second for Llama 70B models, making it significantly faster and more cost-effective than NVIDIA's next-generation GPUs. By focusing exclusively on transformers, Sohu achieves over 90% FLOPS utilization, compared to around 30% on standard GPUs. To put this into perspective, a single 8xSohu server can replace 160 NVIDIA H100 GPUs, highlighting its unprecedented efficiency. Benchmarks with Llama-3 70B in FP8 precision demonstrate Sohu's capability to handle complex computations with great speed and accuracy. At Cofount, we're excited about Sohu's potential to reshape the AI industry, enabling real-time applications and setting new benchmarks for performance. Founded by visionaries Gavin Uberti and Chris Zhu, Sohu represents a groundbreaking leap forward in AI technology. What are your thoughts on this innovation? We'd love to hear your views! #AI #ChatGPT #Llama #Claude #ASIC #Transformers #AIHardware #NextGenChips #LLM #TechInnovation