Semiconductors

Recent analysis, briefs, and signals in this coverage lane.

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Semiconductors

BriefAI InfrastructureSep 30, 2026arXiv

Heddle: Learning Structural Templates for Parallelism Planning on Heterogeneous GPU Clusters

Heddle: Learning Structural Templates for Parallelism Planning on Heterogeneous GPU Clusters gives buyers a sharper read on accelerator supply, memory bandwidth, and performance-per-watt planning; the practical checkpoint is lease timing for the arXiv construction read on Heterogeneous GPU Clusters.

The arXiv update on Heddle: Learning Structural Templates for Parallelism Planning on changes how buyers model accelerator supply, memory bandwidth, and AI infrastructure refresh timing; the exposed dependency is lease timing for the arXiv energized dependency on Heterogeneous GPU Clusters.

OperatorsHyperscalersInvestorsData Scientists

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BriefSemiconductorsSep 21, 2026arXiv

Scalable Packet Tracking on FPGAs for Erasure-Coded RDMA over Lossy WANs

Scalable Packet Tracking on FPGAs for Erasure-Coded RDMA over Lossy WANs puts thermal design and rack-density assumptions back into the capacity plan for AI facilities; the practical checkpoint is construction milestones for the arXiv contracted read on over Lossy WANs.

The arXiv update on Scalable Packet Tracking on FPGAs for Erasure-Coded RDMA over Lossy WANs puts AI infrastructure planning closer to thermal limits, facility design, and customer ramp timing; the exposed dependency is construction milestones for the arXiv delivery test on over Lossy WANs.

OperatorsHyperscalersInvestorsData Center Managers

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BriefAI InfrastructureSep 29, 2026arXiv

VarioPath: Workload-Aware All-to-All Communication for PCIe GPU Clusters

VarioPath: Workload-Aware All-to-All Communication for PCIe GPU Clusters gives buyers a sharper read on accelerator supply, memory bandwidth, and performance-per-watt planning; the practical checkpoint is developer risk for the arXiv facility milestone on PCIe GPU Clusters.

The arXiv update on VarioPath: Workload-Aware All-to-All Communication for PCIe GPU Clusters puts AI infrastructure planning closer to chip allocation, buyer queues, and cloud margin pressure; the exposed dependency is developer risk for the arXiv energized dependency on PCIe GPU Clusters.

OperatorsHyperscalersInvestorsCloud Buyers

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BriefAI InfrastructureSep 28, 2026arXiv

Scepsy: Serving Agentic Workflows Using Aggregate LLM Pipelines

Scepsy: Serving Agentic Workflows Using Aggregate LLM Pipelines gives buyers a sharper read on accelerator supply, memory bandwidth, and performance-per-watt planning; the practical checkpoint is commissioning risk for the arXiv resilience model on Aggregate LLM Pipelines.

The arXiv update on Scepsy: Serving Agentic Workflows Using Aggregate LLM Pipelines gives operators another supplier signal for GPU availability, capacity-per-watt, and procurement timing; the exposed dependency is commissioning risk for the arXiv facility read on Aggregate LLM Pipelines.

OperatorsInvestorsHyperscalersCloud Buyers

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BriefAI InfrastructureSep 28, 2026arXiv

The KV Cache Is the New Memory Wall

The KV Cache Is the New Memory Wall gives buyers a sharper read on accelerator supply, memory bandwidth, and performance-per-watt planning; the practical checkpoint is refresh cycles for the arXiv interconnection model on New Memory Wall.

The arXiv update on The KV Cache Is the New Memory Wall gives operators another supplier signal for GPU availability, capacity-per-watt, and procurement timing; the exposed dependency is refresh cycles for the arXiv utilization read on New Memory Wall.

OperatorsInvestorsHyperscalersSemiconductor Suppliers

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BriefSemiconductorsSep 25, 2026arXiv

HBF-Sim: An Extensible HBF Simulator for Large-scale GPU Memory Systems

HBF-Sim: An Extensible HBF Simulator for Large-scale GPU Memory Systems gives buyers a sharper read on accelerator supply, memory bandwidth, and performance-per-watt planning; the practical checkpoint is substation work for the arXiv commissioning window on GPU Memory Systems.

The arXiv update on HBF-Sim: An Extensible HBF Simulator for Large-scale GPU Memory Systems gives operators another supplier signal for GPU availability, capacity-per-watt, and procurement timing; the exposed dependency is substation work for the arXiv buyer checkpoint on GPU Memory Systems.

OperatorsInvestorsHyperscalersDevelopers

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BriefAI InfrastructureSep 22, 2026arXiv

Accurate Distributed Tracing for Large-Scale AI Infrastructure: Time Synchronization as a Foundation for Reliable Observability

Accurate Distributed Tracing for Large-Scale AI Infrastructure: Time Synchronization as a gives buyers a sharper read on accelerator supply, memory bandwidth, and performance-per-watt planning; the practical checkpoint is customer ramps for the arXiv cloud checkpoint on Foundation Reliable Observability.

The arXiv update on Accurate Distributed Tracing for Large-Scale AI Infrastructure: Time puts AI infrastructure planning closer to chip allocation, buyer queues, and cloud margin pressure; the exposed dependency is customer ramps for the arXiv construction milestone on Foundation Reliable Observability.

OperatorsHyperscalersInvestorsCloud Buyers

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BriefSemiconductorsSep 22, 2026arXiv

SPLASH: Co-Designing Sparse Attention with High-Bandwidth Flash for Efficient Long-Context Inference

SPLASH: Co-Designing Sparse Attention with High-Bandwidth Flash for Efficient Long-Context gives buyers a sharper read on accelerator supply, memory bandwidth, and performance-per-watt planning; the practical checkpoint is lease timing for the arXiv power milestone on Efficient Long-Context Inference.

The arXiv update on SPLASH: Co-Designing Sparse Attention with High-Bandwidth Flash for changes how buyers model accelerator supply, memory bandwidth, and AI infrastructure refresh timing; the exposed dependency is lease timing for the arXiv energized dependency on Efficient Long-Context Inference.

OperatorsHyperscalersInvestorsAI Developers

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BriefAI InfrastructureSep 17, 2026arXiv

COMPASS-ABS: Reducing Fragmentation in Shared GPU Clusters for Deep Learning Training Workloads

COMPASS-ABS: Reducing Fragmentation in Shared GPU Clusters for Deep Learning Training Workloads gives buyers a sharper read on accelerator supply, memory bandwidth, and performance-per-watt planning; the practical checkpoint is power budgets for the arXiv energized test on Learning Training Workloads.

The arXiv update on COMPASS-ABS: Reducing Fragmentation in Shared GPU Clusters for Deep puts AI infrastructure planning closer to chip allocation, buyer queues, and cloud margin pressure; the exposed dependency is power budgets for the arXiv margin signal on Learning Training Workloads.

OperatorsHyperscalersInvestorsCloud Buyers

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BriefAI InfrastructureSep 17, 2026arXiv

OAK: Restart- and Age-Aware Scheduling for Distributed Machine Learning on Shared GPU Clusters

OAK: Restart- and Age-Aware Scheduling for Distributed Machine Learning on Shared GPU Clusters gives buyers a sharper read on accelerator supply, memory bandwidth, and performance-per-watt planning; the practical checkpoint is memory bandwidth for the arXiv capital exposure on Shared GPU Clusters.

The arXiv update on OAK: Restart- and Age-Aware Scheduling for Distributed Machine Learning on changes how buyers model accelerator supply, memory bandwidth, and AI infrastructure refresh timing; the exposed dependency is memory bandwidth for the arXiv delivery constraint on Shared GPU Clusters.

OperatorsInvestorsAI ResearchersHyperscalers

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