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Lambda Cloud adds Nvidia HGX H100 and Quantum-2 InfiniBand clusters Silicon Valley-based GPU cloud company Lambda Labs has introduced Nvidia HGX H100 and Quantum-2 InfiniBand Clusters designed for AI model training. Targeted at AI developers who need high-end AI hardware without long-term rental commitments, these Lambda 1-Click Clusters have a minimum reservation period of two weeks. Robert Brooks, founding team member and VP of revenue at Lambda, highlighted the company's achievement in partitioning large, high-performance AI deployments into smaller GPU clusters available on demand through a self-serve model. This innovation aims to overcome the barriers of GPU availability, long-term contracts, and high costs, facilitating AI breakthroughs. The clusters feature 16 to 512 interconnected Nvidia H100 GPUs with Quantum-2 InfiniBand networking. Dave Salvator, director of accelerated computing products at Nvidia, emphasized the importance of providing powerful, accelerated computing access to a wide range of teams to achieve transformative AI across industries. #lureit #wannabelured #hardware #software #network #base #data #it #project #development #company #digital #power #launch #solution #gpu #chip #infiniband #nvidia #power #construction #clusters #datacenter

For over half a century, general-purpose processors have been built on the Tomasulo algorithm, developed by IBM engineer Robert Tomasulo in 1967. It’s a $500B industry built on specialized CPU, GPU, and other chips for different computing tasks. Hardware startup Ubitium has shattered this paradigm with a breakthrough universal processor that handles all computing workloads on a single, efficient chip… #riscv #ai #semiconductor #chip #processors

RETRANSMISSION: HIVE Expands NVIDIA Chip Suite to Power AI Boom with $30 Million H100 and H200 GPU Clusters to be Deployed in Quebec #PressReleases #boom #Chip #Clusters #deployed #expands #GPU #H100 #H200 #hive #million #News8PlusPressRelease #nvidia #power #Quebec #retransmission #Suite

From unparalleled parallel processing capabilities of NVIDIA GPUs to the energy-efficient versatility of Arm chips, Supercharge your computational workflows on Rescale. Author: My esteemed colleague Sam Zakrzewski 🚀

I recently attended International Symposium on Computer Architecture (ISCA) and noticed that people showed much interest in Machine Learning accelerators. Especially if the accelerator is for LLMs, it catches much more attention. I was surprised since, as long as the machine learning landscape changes so quickly, we do not have a better option than GPUs for their acceleration. GPUs provide generality while being more optimized than a CPU or FPGA for this kind of workload. This is why main companies are using them, and this is why NVIDIA's stock is skyrocketing. I see lots of potential to optimize GPUs for this kind of workload; they are still an infant in this area. Optimizing them for these workloads is not only in the interest of companies, but it also helps the machine learning models become mature faster. In addition, if we make GPUs more efficient for these workloads, we have contributed to saving the environment from all their demanding computation. However, as long as people don't show any interest in research in this direction, we are far from reaching there. I would be glad to read your comments about this. #ISCACONF, #ISCA2024, #LLM, #Transformers, #Bert, #llama2, #bart, #openai, #chatgpt, #gemini, #NVIDIA, #computerarchitecture, #GPU, #GPGPU, #Micoarchitecture

#AI chipmakers Cerebras and #SambaNova have announced cloud inference API offerings based on their specialized hardware, joining Groq to compete with hyperscaler and startup offerings based on #Nvidia #GPUs. All three #chipmakers are offering much faster single-user tokens-per-second on language model Llama versus Nvidia GPU-based clouds. Groq started talking about its tokens-per-second figures earlier this year, with results many multiples of any other offering at the time, and went viral for it. Others are now following suit, with tokens-per-second and tokens-per-dollar emerging as new de facto benchmarks for AI offerings. #Benchmarks from Artificial Analysis show Cerebras’ Llama3.1-8B can offer 1800 tokens/s; previous record holder SambaNova had 1084 tokens/s on the same model and Groq had 750 tokens/s. For the larger Llama3.1-70B, SambaNova is currently claiming the crown with 580 tokens/s versus Cerebras’ 445 and Groq’s 544 tokens/s. Of the three, only SambaNova offers an API for the largest Llama3.1-405B model, and its speeds are above 100 tokens/s at 16-bit precision. These figures change weekly or even daily as the companies strive to optimize their software and leapfrog each other in terms of performance. All three startups currently engaged in “token wars” are clear in their messaging: Nvidia GPUs, which power all hyperscaler inference APIs available today, cannot deliver these kinds of speeds. According to Artificial Analysis, Llama3.1-8B running on various Nvidia H100-based systems at hyperscalers and domain-specific cloud providers managed a minimum of 72 tokens/s and a maximum of 257 tokens/s. AWS was benchmarked at 93 tokens/s on the same workload, for example. #IndustrialElectronics #SemiconductorElectronic #QualityAssurance #ElectronicComponentsDistributor #ElectronicsProducts #ObsoletePartsProcurement #icindustry #semiconductordevelopment #supplying #Capacitors #ICs #EmbeddedProcessors #Divider #Multiplier #WidebandSynthesizer #OutputRegulator #Microcontroller #CommunicationICs #Isolators #DisplayController #EectronicComponentsProcurement #BuyElectronicParts #ic #chip #semiconductor #supplying #distributor #electroniccomponentsdistributor #spot #ti #micron #tdk #nxp #xilink #intel #ADI #Alterla #military #auotmotive #ems #oem #odm #medical #communication #icchip #chips #electronics #components #purchasing #holt #vicor #altera #xilink #adi #ti

https://lnkd.in/ggN62AkR Micron’s Partnership With NVIDIA For H200 AI GPUs Shocks SK Hynix & Others In The HBM Race. Korean media reports that Team Green's decision to opt for Micron's HBM3e process for its H200 AI GPU has stirred up a new debate among HBM manufacturers as Micron grasps the holy grail of next-gen markets. #micron #nvidia #artificialintelligence #llms #generativeai #gpu #servers #datacenter #cloud #ai #Semiconductorindustry #electronics #semiconductor #supplychain #engineering #manufacturing #technology #computerchips #business #innovation #semiconductors #chips #chipmaker #foundry credit: wccftech

HIVE Expands NVIDIA Chip Suite to Power AI Boom with $30 Million H100 and H200 GPU Clusters to be Deployed in Quebec #PressReleases #boom #Chip #Clusters #deployed #expands #GPU #H100 #H200 #hive #million #News8PlusPressRelease #nvidia #power #Quebec #Suite

High-performance computing (HPC) has become the essential instrument of scientific discovery. Whether it is discovering new, life-saving drugs, battling climate change, or creating accurate simulations of our world, these solutions demand an enormous (and rapidly growing) amount of processing power. That is why industry has embraced NVIDIA GPU-accelerated computing. Combined with AI, it is bringing millionfold leaps in performance for scientific advancement. #data #cloud #simulation #modelling #hpc #nvidia #NVLink #benchmark #multigpu #design #scientificcomputing #datacenter

Gigabyte MGX server with GH200 superchip #GIGABYTE #GigaComputing #GIGABYTEServer #HPC #DataScience #MachineLearning #AIserver #MGX #Accelarating #ArmServer #NewEraOfAI #ScalableDataCenter