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.
➡️ https://t.co/ISz9Y5Uw5H
@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: https://t.co/NZbUIJqPc8
🔧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: https://t.co/U25Ru5Jc8l
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 ➡️ https://t.co/ZjbCkPGXmJ
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
🤖 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! https://t.co/vRM8uVRX5a
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: https://t.co/hR20YgJFgp
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 https://t.co/Q6ecxH2D2U 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.
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: https://t.co/lLbcFrsYh3
🧵 4/4
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.
🧵 1/4
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.
🧵 3/4