ML Commons MLPerf® Training 4.0 benchmarks are now live.
Click the link to read how we've proven to save up to 50% total energy whilst maintaining industry-leading benchmark training performance.
➡️ bit.ly/3KHl6Qs
@MLCommons #Sustainable #AI #Llama #GPT3
By accelerating AI inference efficiently, we're helping businesses make smarter decisions faster—at a fraction of the usual energy footprint.
Using MLPerf's Inference Benchmarks to measure process outputs, when compared to industry giants, SMC sits in the top 5% of performers.
🇦🇺 Australia, it’s nearly time. Good luck to all teams participating in Stage 1 of The Generative AI CodeFest 👍
Key Date - Stage 1: Friday, November 29, 2024 [09:00 AM - 12:30 PM]
#Hackathon #AI #GPUcloud
Thrilled to be celebrating with Firmus Technologies—we're a finalist for the DCD Awards: Asia Pacific Data Center Project of the Year! We’re honoured to be recognised for our Sustainable HyperCube Deployment, in collaboration with ST Telemedia Global Data Centres. 🌱
Using our patented immersion cooling technology, we cut CO2 by 3.8 tonnes per H100 per year. 🌱
Learn about the benefits and types of immersion cooling, as well as an in-depth understanding of single-phase immersion cooling here: youtu.be/zzi3WoNstwQ
🔧Designed to keep your AI services optimized, resilient, and ready to scale, SMC’s support transforms AI infrastructure management, making it as seamless as it is sustainable.
#SustainableAI #GPUCloud
Our systems are among the fastest at processing inputs and delivering real-time results using trained models — reviewed alongside industry giants like Dell, Microsoft, NVIDIA, Oracle, and Google.
AI enthusiasts in Australia, here's your chance to bring your concepts to life.
𝐇𝐚𝐜𝐤𝐚𝐭𝐡𝐨𝐧 𝐝𝐚𝐭𝐞𝐬: November 29 - December 06, 2024
𝐑𝐞𝐠𝐢𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧 𝐝𝐞𝐚𝐝𝐥𝐢𝐧𝐞: Tuesday, November 05, 2024
Learn more: bit.ly/3Nviuqt
Electrical & Controls Engineer, Ken Ng, talks about his experience so far:
🌱 Deploying the first Sustainable AI Factory in Singapore
🚀 Leveraging AI algorithms to further boost efficiency
🌏 A recent work rotation in Tasmania
Read his interview here ➡️ bit.ly/3U98ire
NVIDIA-powered GPU clusters that are optimised for AI training and deployment with supporting applications like TensorFlow, PyTorch, RAPIDS, and more. Take your AI projects to the next level — sustainably. 🌱
#AI #GPUCloud #NVIDIA #TensorFlow #PyTorch #RAPIDS #SustainableAI
Sustainable Metal Cloud (SMC) retweeted
🤖 Calling all #AI enthusiasts in SEA! Join the #generativeAI Hackathon hosted by @OpenACCorg, NVIDIA and @SMC_FutureAI. Learn from NVIDIA experts and gain hands-on skills. Registration closes on Oct. 13. Register now! nvda.ws/4eaTZu9
Are you an AI enthusiast, keen to build some real-world impact?
𝐇𝐚𝐜𝐤𝐚𝐭𝐡𝐨𝐧 𝐝𝐚𝐭𝐞𝐬: October 29 - November 15, 2024
𝐑𝐞𝐠𝐢𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧 𝐝𝐞𝐚𝐝𝐥𝐢𝐧𝐞: October 13, 2024 (less than 2 weeks away!)
➡️ Learn more: bit.ly/3BpKqZT
Our Solutions Architect, Derek Ngo, discusses tackling deployment challenges, MLPerf results, and details of our immersion cooling technology.
Read more: bit.ly/3NqCVox
At SMC, we’re not just moving fast—we’re moving with purpose.
Hear from our team, sharing what they love about working at SMC.
💼 We're hiring. Visit smc.co/careers for more.
#Sustainable #AI #GlobalImpact #SMC
Our GPU clusters are built for ultimate reliability, delivering enterprise-grade performance alongside strict compliance (SOC 2 compliant). With unmatched network capabilities and dedicated resources, security and flexibility go hand in hand.
Our energy cost advantage allows Sustainable Metal Cloud to be globally price competitive, regardless of location. 🌏
#AI #CloudComputing #Sustainability #CostEfficiency
𝐈𝐭'𝐬 𝐭𝐢𝐦𝐞 𝐭𝐨 𝐫𝐞𝐭𝐡𝐢𝐧𝐤 𝐃𝐂 𝐞𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲 𝐦𝐞𝐭𝐫𝐢𝐜𝐬. 𝐏𝐔𝐄 𝐬𝐢𝐦𝐩𝐥𝐲 𝐢𝐬𝐧'𝐭 𝐞𝐧𝐨𝐮𝐠𝐡 𝐚𝐧𝐲𝐦𝐨𝐫𝐞.
As AI workloads grow, traditional metrics like Power Usage Effectiveness (PUE) are no longer sufficient to gauge true efficiency.
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A question then arises, "Is there a way to determine power efficiency at a more granular level than what PUE offers?"
This year’s MLPerf benchmarks not only added tests for two generative AI models but also invited contributions regarding energy consumption.
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In the MLCommons-verified report released in July, SMC’s GPT-3 175B, 512 H100 Tensor Core GPUs submission consumed only 468 kWh of total energy when connected with NVIDIA Quantum-2 Infiniband networking.
🔗 Read more: bit.ly/47eJkMm
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