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  1. Home
  2. /Repositories
  3. /beam-cloud/beta9
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repoGitHubTrust 82 · PrimaryPublished 1mo agoLive · yesterday

beam-cloud/beta9

Ultrafast serverless GPU inference, sandboxes, and background jobs

Lineage graph

Paper → model → repo connections mined from source citations (Tier-1 exact match).

Why these links exist

Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.

  • PossiblePossibly related (embedding) · 57%Hardware startup unveils inference accelerator →
  • PossiblePossibly related (embedding) · 48%Cerebras OpenAI deal capacity has effectively killed the waitlist for everyone else [D] →
  • PossiblePossibly related (embedding) · 47%SoftBank enters the rent-a-GPU race as America looks for support for AI training →
  • PossiblePossibly related (embedding) · 47%Spot/interruptible H100 and A100 pricing across RunPod, Vast.ai, and AWS - June 2026 data [D] →
  • PossiblePossibly related (embedding) · 47%One-Step Gradient Delay is Not a Barrier for Large-Scale Asynchronous Pipeline Parallel LLM Pretraining →
  • PossiblePossibly related (embedding) · 53%WattGPU: Predicting Inference Power and Latency on Unseen GPUs and LLMs →
  • PossiblePossibly related (embedding) · 57%GPUHedge: Hedging serverless GPU providers improves cold start p95 latency from 117s to 30s [P] →
  • PossiblePossibly related (embedding) · 50%Understanding GPU Inference Workloads [D] →

Covers

newsHardware startup unveils inference acceleratornewsCerebras OpenAI deal capacity has effectively killed the waitlist for everyone else [D]newsSoftBank enters the rent-a-GPU race as America looks for support for AI trainingnewsSpot/interruptible H100 and A100 pricing across RunPod, Vast.ai, and AWS - June 2026 data [D]

Implements

paperOne-Step Gradient Delay is Not a Barrier for Large-Scale Asynchronous Pipeline Parallel LLM Pretraining

Implements (incoming)

paperWattGPU: Predicting Inference Power and Latency on Unseen GPUs and LLMs

Covers (incoming)

newsGPUHedge: Hedging serverless GPU providers improves cold start p95 latency from 117s to 30s [P]newsUnderstanding GPU Inference Workloads [D]

Related across the graph

newsSoftBank enters the rent-a-GPU race as America looks for support for AI trainingnewsCerebras OpenAI deal capacity has effectively killed the waitlist for everyone else [D]newsGPUHedge: Hedging serverless GPU providers improves cold start p95 latency from 117s to 30s [P]paperWattGPU: Predicting Inference Power and Latency on Unseen GPUs and LLMsnewsUnderstanding GPU Inference Workloads [D]newsHardware startup unveils inference acceleratornewsSpot/interruptible H100 and A100 pricing across RunPod, Vast.ai, and AWS - June 2026 data [D]paperOne-Step Gradient Delay is Not a Barrier for Large-Scale Asynchronous Pipeline Parallel LLM Pretraining
Knowledge path·NSoftBank enters the rent-a-GPU race as America looks for support for AI training→NCerebras OpenAI deal capacity has effectively killed the waitlist for everyone else [D]→NGPUHedge: Hedging serverless GPU providers improves cold start p95 latency from 117s to 30s [P]→Rbeam-cloud/beta9

Topics

autoscalercloudruncudadeveloper-productivitydistributed-computingfaasfine-tuningfunctions-as-a-servicegenerative-aigpu

Explore

Search similar →Knowledge graph →All repos →Full intelligence feed →
Graph trust82Primary
Graph score1744