Alternatives
Products that do what I made a calculator to show cost savings of serverless GPUs vs. AWS does
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2020 · duckbillgroup.com
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Greetings HN! This is Doruk from Oblivus, and I'm excited to announce the launch of our platform, Oblivus Cloud. After more than a year of beta testing, we're excited to offer you a platform where you can deploy affordable and scalable GPU virtual machines in as little as 30 seconds! https://oblivus.com/cloud - What sets Oblivus Cloud apart? At the start of our journey, we had two primary goals in mind: to democratize High-Performance Computing and make it as straightforward as possible. We understand that maintaining GPU servers through major cloud service providers can be…
2023 · oblivus.com
- 4TC
Hello HN! I’m Jonathan from TensorDock. After 7 months in beta, we’re finally launching Core Cloud, our platform to deploy GPU virtual machines in as little as 45 seconds! https://www.tensordock.com/product-core Why? Training machine learning workloads at large clouds can be extremely expensive. This left us wondering, “how did cloud ever become more expensive than on-prem?” I’ve seen too many ML startups buy their own hardware. Cheaper dedicated servers with NVIDIA GPUs are not too hard to find, but they lack the functionality and scalability of the big clouds. We thought to…
2022 · tensordock.com
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2021 · cloudshim.com
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2019 · github.com
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The standard GPU utilization metric reported by nvidia-smi, nvtop, Weights & Biases, Amazon CloudWatch, Google Cloud Monitoring, and Azure Monitor is highly misleading. It reports the fraction of time that any kernel is running on the GPU, which means a GPU can report 100% utilization even if only a small portion of its compute capacity is actually being used. In practice, we've seen workloads with ~1–10% real compute throughput while dashboards show 100%. This becomes a problem when teams rely on that metric for capacity planning or optimization decisions, it can make underutilized systems…
Apr 2026 · systalyze.com
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2021 · gpu.land
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2012 · kloudcalc.com
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Hey HN: Kaveh here, the founder of https://www.usage.ai/ We launched on Hacker News for the first time early last year, and we've made a lot of progress since then. We've saved tens of millions of dollars for companies, and we are even more excited to announce the launch of a new product: insured reservations for RDS! We worked closely with AWS on this feature and are excited to finally make it generally available. We help companies drive down AWS EC2 & RDS spend. Why? Because the way it's done now is a pain. DevOps and Software Engineers end up spending time managing costs…
2023
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2023 · vram.asmirnov.xyz
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Hey folks, my name is Owen and I recently started working at a startup (https://infracost.io/) that shows engineers how much their code changes are going to cost on the cloud before being deployed (in CI/CD like GitHub or GitLab). Previously, I was one of the founders of tfsec (it scanned code for security issues). One of the things I learnt was if we catch issues early, i.e. when the engineer was typing their code, we save a bunch of time. I was thinking … okay, why not build cloud costs into the code editor. Show the cloud cost impact of the code as the engineers are…
2024
- 15TC
2020 · npmjs.com
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Affordable H100, H200, GB300, and B200 GPU compute for training, inference, and everything in between.
4d ago · compute.cheap
- 18IB
Hey HN: Kaveh here, the founder of https://www.usage.ai/ We help companies drive down AWS EC2 spend. Why? Because the way it's done now is a pain. DevOps and Software Engineers end up spending time managing costs rather than focusing on business problems. Previous to founding Usage, I worked on high-performance computing research at JP Morgan Chase and as a software engineer at a number of smaller startups. Here's how it works: We are typically brought in by a DevOps manager to cut AWS EC2 costs. The app is entirely self-service and the savings are generated automatically,…
2022 · usage.ai
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Hi HN, we are Ed, Zach, and Ronald, creators of Shadeform (https://www.shadeform.ai/), a GPU marketplace to see live availability and prices across the GPU market, as well as to deploy and reserve on-demand instances. We have aggregated 8+ GPU providers into a single platform and API, so you can easily provision instances like A100s and H100s where they are available. From our experience working at AWS and Azure, we believe that cloud could evolve from all-encompassing hyperscalers (AWS, Azure, GCP) to specialized clouds for high-performance use cases. After the launch of…
2023 · shadeform.ai
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2015 · github.com
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- 24GC
2022 · gcloud-compute.com
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