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Earlier sources: Compute
This hardware thread follows compute through original research, public projects, and source reports. Read the evidence below to see which developments are represented in SYMTRI’s archive.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗26 classified signals in the fourteen-day window. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- arXiv · Published · First archived
Control-Compute Governance in Agentic AI-RAN: AI Agents as Both Controllers and Workloads ↗
Recent advances in artificial intelligence-radio access network (AI-RAN) are placing large language model (LLM)-driven agents within the open RAN (O-RAN) control hierarchy. A promising deployment for this agentic AI-RAN co-locates LLM inference with physical-layer (PHY) communication processing over the same accelerated compute pool for infrastructure sharing, data locality, and low control latency. However, this co-location induces bidirectional control-compute coupling, as the agent competes with PHY processing for compute, while its reasoned gNB control actions may alter future PHY workload…
- Hacker News · Posted on Hacker News · First archived
Semantic Compute: From Interpreters to Compilers ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Whistle: Speech to Text in 16.9 MB by Cactus Compute ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Show HN: Enki – Write GPU compute kernels in pure stable Rust ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
American Compute – Data Center Financing Risk Management Solutions ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Trading off compute for memory with activation checkpointing ↗
Hacker News discussion.
- Hacker News · Posted on Hacker News · First archived
Ask HN: What to do with lots of spare compute in colocation? ↗
I moved my homelab into a colocation rack (proper DC deployment with redundant power) a while ago. Things have been running smoothly, and a few favorable 2nd hand deals later I now have 128 cores (Epyc Zen 2), roughly 1TB of RAM and several dozen TBs flash and spinning storage running idle. It's all on spare enterprise-grade hardware (15th generation Dell PowerEdge, redundant SAS SSD/HDD arrays), interconnected with 25G. Uplink is 10G. It's utili…
- OpenAlex · Published · First archived
RL-Axial: Learning When to Compute Global Context for Multimodal Segmentation ↗
High-resolution remote sensing semantic segmentation is a key enabler for fine-grained urban mapping and related geospatial applications. However, complex textures, severe scale variations, and cross-modal discrepancies make models with fixed architectures and computation paths struggle to combine reliable multimodal fusion with adequate global-context modeling. To address these challenges, we propose RL-Axial, a multimodal segmentation framework with interpretable, sample-adaptive context aggregation. A cross-modal gated fusion head (CMGF) performs pixel-wise fusion between RGB and digital su…
- OpenAlex · Published · First archived
A Scalable and Efficient Hardware Accelerator for Realtime EMG-based Gesture Recognition using Deep Learning ↗
Abstract Real-time hand gesture recognition from surface electromyography (sEMG) is a key enabling technology for myoelectric prostheses. Deploying accurate deep learning models on resource-constrained wearable hardware remains a central challenge. This paper evaluates the OpenEye FPGA accelerator for inference of a multi-scale 1D-CNN on the Ninapro DB2 benchmark dataset recorded from healthy subjects. We characterize classification accuracy across a hyperparameter grid (kernel configuration, window size, pool size) and assess the impact of post-training INT8 quantization. OpenEye achieves inf…
- OpenAlex · Published · First archived
StEdge: A Low-Power Real-Time Hardware Accelerator for Edge Detection Using Stochastic Computing ↗
Edge detection is a fundamental operation in real-time image and video processing systems. However, conventional gradient-based hardware implementations incur significant power, area, and computational overheads. This work presents StEdge, a low-power, configurable hardware accelerator for real-time edge detection based on stochastic computing (SC), supporting both Sobel and Prewitt gradient operators within a unified architecture. The proposed design reformulates gradient computation in the stochastic domain, replacing arithmetic-intensive operations with lightweight logic gates. To further r…
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How to assess evidence about Compute
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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