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Türkçe sürüme geçSemiconductor design, manufacturing, equipment and supply chains for chip raw materials. Page 3.
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A preprint presents LENS, a system for camera localization and neural scene rendering on an AMD KR260 FPGA and ARM platform. The work adapts a scene-coordinate and Gaussian-splatting pipeline to an edge device, with the goal of operating without a desktop GPU.
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A preprint describes a workflow for mapping a small neural simulation of Caenorhabditis elegans to Intel’s Loihi-2 neuromorphic hardware through NeuroML2Loihi. The study addresses the cost of repeatedly updating neural and synaptic states in software.
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Researchers introduce PACT, a system for LoRA fine-tuning on consumer GPUs that uses native NVFP4 matrix operations for frozen projections. The paper also addresses memory spent on activations and the cost of quantizing and dequantizing data.
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EdgeKernelBench studies whether large language models can generate kernels for varied edge-computing hardware. The preprint introduces a common intermediate representation and a hierarchical benchmark that connects workloads to different backends.
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A preprint introduces Koi, a cluster planner for large language model inference across heterogeneous multi-cloud fleets. It considers accelerator choice, parallelization, serving engines, replica counts and changing workloads as interdependent operating decisions.
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A research preprint introduces Muse Glimmer, an open-source 30-billion-parameter causal language model with a perception encoder for agent tasks on consumer hardware. The authors describe text and image input, multi-step reasoning, tool use and failure recovery.
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The preprint examines whether smartphone neural processing units can help fine-tune language models locally with low-rank adaptation. It focuses on the repeated operations involving frozen model weights that remain costly even when only a small number of parameters are trained.
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The authors examine whether the matrix-vector processor inside a commodity EFR32MG24 microcontroller can accelerate sparse spiking-neural-network inference beyond an optimized Cortex-M33 CPU. Their toolchain maps snnTorch models to C and reorders neurons to improve accelerator use.
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The University of North Texas says its new project phase will test candidate materials for infrared sensors and examine whether they can be made with existing semiconductor processes.
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An October 9 preprint coauthored by a University of Maryland researcher examines the topology and angular magnetoresistance of hexagonal TiAs crystals grown by chemical vapor transport.
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An October 9 preprint from BITS Pilani Dubai uses first-principles calculations to predict phononic frequency combs in two twisted transition-metal dichalcogenide heterostructures.
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An October 9 preprint from a University of Massachusetts Boston researcher describes a sensor layout integrating a laser, photodiode and readout electronics on sapphire.
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