Search: “hardware”

FlashRT: Agent Harness for Guiding Agents to Deploy Real-Time Multimodal Applications

arXiv:2607.18171v2 Announce Type: replace Abstract: Real-time multimodal applications, including voice agents and interactive video generation, compose heterogeneous models into pipelines whose effici

11 Aug 2026

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Hardware

What Irregularity Costs: CUDA C++, Rust, and Triton on a Hash-Blocked GPU Workload

DGX agent

arXiv:2608.08287v1 Announce Type: new Abstract: GPU language comparisons are almost always run on tiled dense linear algebra, where every toolchain is good and the differences are small. We implement

hardwarearxiv-cs-cv

11 Aug 2026

Beyond Visibility: Real-Time Surface Accessibility Fields from Sparse LiDAR

arXiv:2608.06412v1 Announce Type: cross Abstract: Understanding which surfaces in a scene are physically accessible to a given tool is fundamental for robotic interaction, yet 3D perception systems ty

hardwarearxiv-cs-ro

10 Aug 2026

Introducing the Developer Device Platform for agentic mobile app development

model-releasesgoogle-cloud-ai

Most enterprises connect with their customers through a device. Whether it’s using a mobile app to order a product, contact customer service, view content, or manage their account, the customer experi

10 Aug 2026

SparseDitto: Customizing GPU Kernels for Different Sparsity Patterns with LLM-Based Agentic System

arXiv:2608.05033v1 Announce Type: cross Abstract: Sparse matrix kernels are fundamental to scientific computing, graph analytics, and machine learning. Their GPU performance depends strongly on the in

6 Aug 2026

A Deployment-Friendly Foundational Framework for Efficient Computational Pathology

arXiv:2602.14010v2 Announce Type: replace-cross Abstract: Pathology foundation models (PFMs) generalize well across computational pathology tasks but remain costly for gigapixel whole-slide image anal

5 Aug 2026

SparseKAN: Compressing Kolmogorov--Arnold Networks Across Basis Functions, Neurons, and Bits

arXiv:2608.00859v1 Announce Type: new Abstract: Kolmogorov--Arnold Networks (KANs) replace scalar edge weights with learnable univariate functions parameterized by multiple basis coefficients. This in

4 Aug 2026

Research

Thermalizing Stochastic Programs

arXiv:2608.01615v1 Announce Type: cross Abstract: We present a set of tools for mapping general stochastic programs to thermodynamic hardware designed for energy-efficient stochastic sampling. Given a

researcharxiv-cs-lg

4 Aug 2026

'Data center in a Box (on Wheels)' 256Gb VRAM/512Gb RAM AI Server 6-8 Month Operational Review, Stability Write Up, Benchmarks

model-releasesr-localllama

I've been out of these forums for awhile but I figured I would provide a formal update on how this has been going now that it has some operation time under its belt, just to put the information out th

DeepSeek V4-Flash (284B MoE) at 33 tok/s single / 68 tok/s aggregate on 2× RTX 3090 + a used quad-Xeon DDR4 server — full config

model-releasesr-localllama

Ran DeepSeek V4-Flash-0731 — the full official checkpoint, not a re-quant — on commodity used hardware. Sharing because I couldn't find anyone else publishing Ampere results for this engine. Why bothe

DeltaServe: Host-Agnostic Co-Serving of Inference and Fine-Tuning for LLMs

arXiv:2607.28848v1 Announce Type: cross Abstract: LLM serving systems are provisioned for peak load to meet strict latency targets, leaving substantial GPU compute idle whenever traffic falls below pe

How to Run Isolated Tenant Kubernetes Clusters on Shared GPU Infrastructure

A combined architecture using KAI Scheduler and vCluster enables multiple teams to run fully isolated Kubernetes tenant clusters on a shared GPU node, each with its own control plane, RBAC, CRDs, and

Topology-Aware Data Movement for Disaggregated GPU Inference

arXiv:2607.28633v1 Announce Type: cross Abstract: Disaggregated LLM inference creates a datacenter networking problem that no existing system solves correctly. When prefill and decode run on separate

Vivid depiction of a dark scenario for Nvidia. “Indeed, CEO Jensen Huang has been so aggressive in funding the AI ecosystem that the company…

Vivid depiction of a dark scenario for Nvidia. “Indeed, CEO Jensen Huang has been so aggressive in funding the AI ecosystem that the company is functioning almost like a bank; with annual free cash fl

hardwaregary-marcus--x

1 Aug 2026

Co-Designing AI Model Attention for Fast, Interactive Long-Context Inference

The article shows that dense‑attention performance in long‑context inference is governed by group size (query heads per KV head), head dimension, and sequence length, with prefill being compute‑bound

FasTac: A Curved Multispectral Vision-Based Tactile Sensor for High-Speed High-Precision 3D Shape and Force Perception

arXiv:2607.28416v1 Announce Type: new Abstract: Curved tactile fingertips for dexterous manipulation must resolve fine contact geometry, distinguish normal and tangential loads, and capture transient

hardwarearxiv-cs-ro

KernelGenBench: A Multi-Source and Multi-Chip Benchmark for LLM-based Kernel Generation

model-releasesarxiv-cs-lg

arXiv:2607.27231v1 Announce Type: cross Abstract: Large language models (LLMs) have significantly increased the demand for efficient accelerator kernels, but kernel development remains a highly specia

QAdapt: A Noise-Adaptive Neural Pre-Decoding Framework for Quantum Error Correction

model-releasesarxiv-cs-lg

arXiv:2607.28422v1 Announce Type: new Abstract: Fault-tolerant quantum computing (FTQC) relies on quantum error correction to suppress physical errors and preserve logical information at scale. In pra

Applications

WIDE: Boosting Adaptive LLM Inference via Token-level Dynamic Width Pruning

arXiv:2607.28418v1 Announce Type: cross Abstract: Pruning is a promising approach for improving the efficiency of LLMs. Existing static structured pruning methods are hardware-friendly and can deliver

applicationsarxiv-cs-cl

Run High-Performance Core Math at Scale with NVIDIA nvmath-python

NVIDIA **nvmath‑python v1.0** is a Python library that wraps CUDA‑X and NVPL math libraries (cuFFT, cuBLASLt, cuDSS, cuSPARSE, cuTENSOR, cuBLASMp) to give NumPy, CuPy, and PyTorch users GPU‑accelerate

30 Jul 2026

Safety

When Does Legacy Data Start to Help? Emergent Transfer in Cross-Configuration Robot Learning

arXiv:2607.25593v1 Announce Type: new Abstract: Robotic hardware evolves over time, but demonstration data is often tied to a specific sensor and actuator configuration. This raises a practical and un

safetyarxiv-cs-ro

29 Jul 2026

A Motion-Aware Vector Quantization Framework with Centroid Reuse for Efficient VLA Inference

arXiv:2607.24148v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have demonstrated strong potential for embodied AI, yet their high inference latency on GPUs limits real-time deploy

Certified Parallel-in-Time Sinkhorn for Dynamic Entropic Optimal Transport

arXiv:2607.24741v1 Announce Type: cross Abstract: Dynamic applications, including optimal-transport Flow Matching, repeatedly solve related entropic optimal transport problems, yet conventional distri

Energy Constrained Hierarchical Underwater Monitoring via Local Multi-Agent RAG

arXiv:2607.24313v1 Announce Type: cross Abstract: Marine life monitoring is limited by strict energy constraints, poor underwater connectivity, and the high cost of transmitting raw multimodal data fr

Multi-primitive in-memory computing for Monte Carlo tree search

arXiv:2607.22869v1 Announce Type: cross Abstract: Monte Carlo tree search (MCTS) enables artificial intelligence (AI) decision-making, but requires 55-300 W on conventional processors, limiting edge d

Real-Time Semantic Segmentation with Optimized RetinaNet Architectures for Embedded Automotive Systems

arXiv:2607.22714v1 Announce Type: cross Abstract: Real-time perception is a foundational requirement for advanced driver assistance systems (ADAS) and autonomous vehicles, yet embedded automotive plat

Rendering on Real Silicon: GPU Render-Timing as a Passive, AI-Resistant CAPTCHA Signal

arXiv:2607.23389v1 Announce Type: cross Abstract: Conventional CAPTCHAs pose puzzles that modern AI systems increasingly solve, while behavioral and cryptographic-attestation defenses carry privacy or

RIS-Kernel: A Model-Agnostic Architecture for Long-Context LLM Inference via Sparse Attention

arXiv:2607.21927v1 Announce Type: new Abstract: Full self-attention in large language models scales as O(N^2), which limits long-context document analysis to 65,536 tokens and requires costly GPU clus

27 Jul 2026

Can AMD break the CUDA Moat? AMD Advancing AI 2026

AMD’s AI accelerator software stack has progressed sharply, moving from a 0 % chance of catching Nvidia’s CUDA moat in early 2025 to a “great chance” of success by July 2026 after leadership changes a

hardwaresemianalysis

25 Jul 2026

Ms. Forcing: Efficient Streaming Video Generation with Multi-Scale Patchification and Attention

arXiv:2607.20940v1 Announce Type: new Abstract: Streaming video diffusion models have made substantial progress toward interactive and dynamic world simulation, but the nested autoregressive and denoi

24 Jul 2026

SANA-Video 2.0: Hybrid Linear Attention with Attention Residuals for Efficient Video Generation

arXiv:2607.21553v1 Announce Type: new Abstract: We introduce SANA-Video 2.0, a hybrid video diffusion transformer instantiated at 5B and 14B scales under a unified architecture. Designed to generate h

24 Jul 2026

AMD debuts next-generation AI infrastructure for frontier models, agentic workloads and autonomous robots

Advanced Micro Devices Inc. is pushing harder than ever to grab even more market share from Nvidia Corp. in the artificial intelligence chip industry. At its Advancing AI 2026 event today in San Franc

hardwaresiliconangle

From Pixel to Prognosis: Convolutional and GLCM Feature Fusion for Automated Four-Class Cataract Severity Classification

arXiv:2607.18349v1 Announce Type: new Abstract: Objective: To develop a low-cost automated cataract severity classification system operating on standard consumer-grade colour photographs of the eye, w

Research

Integrity of peer-to-peer distributed LLM inference under malicious nodes

arXiv:2607.19490v1 Announce Type: cross Abstract: Peer-to-peer distributed inference executes a Large Language Model (LLM) on pooled consumer hardware by spreading its layers across many nodes. Every

researcharxiv-cs-ai

Leveraging ECRAM for Edge Continual Learning

arXiv:2607.19661v1 Announce Type: cross Abstract: Several edge computing platforms, such as autonomous vehicles and smart sensing devices, need to adapt to dynamic environments in real time by learnin

MoA-Structured Decode Attention DNF Derivation, KV-Cache Accumulation, GQA/MQA, and OpenACC Kernel

arXiv:2607.19456v1 Announce Type: cross Abstract: We derive four memory-optimal inference artifacts for transformer attention using the Mathematics of Arrays (MoA), each following directly from the fo

Setting a World Record for MoE Pre-Training on NVIDIA GB300 NVL72

The NVIDIA GB300 NVL72 platform set a world record by delivering 1,648 TFLOPs per GPU during the pre‑training of DeepSeek‑V3 671B, a mixture‑of‑experts (MoE) model. This achievement leveraged fifth‑ge

21 Jul 2026

The first Vera Rubin clusters are here! Yesterday, @IneffableLabs took delivery of their Vera Rubin NVL72 cluster from @googlecloud @nvidia …

The first Vera Rubin clusters are here! Yesterday, @IneffableLabs took delivery of their Vera Rubin NVL72 cluster from @googlecloud @nvidia The AI frontier jumps forward by yet another generation of h

hardwaresonya-huang--x

21 Jul 2026

NVIDIA NVLink: The Scale-Up Network for AI Factories

NVIDIA’s sixth‑generation NVLink is a purpose‑built scale‑up network that delivers up to 3.6 TB/s per GPU and 260 TB/s rack‑level bandwidth with 130 TFLOPS in‑network compute—outperforming off‑the‑she

20 Jul 2026

Bake It Till You Make It: Ultrafast Spatial Texture-Atlas Splatting

arXiv:2607.13808v1 Announce Type: new Abstract: Recent extensions of 3D Gaussian Splatting (3DGS) capture fine color details using hash-grid-based appearance parameterization but incur high computatio

16 Jul 2026

BREAKING: Dylan Patel (@dylan522p) of @SemiAnalysis_ says 'chips in Europe have less seasoning than chips in America & Mexico.' Plus: › Data…

BREAKING: Dylan Patel (@dylan522p) of @SemiAnalysis_ says 'chips in Europe have less seasoning than chips in America & Mexico.' Plus: › Data centers & France’s nuclear power › AI infrastructure over-o

hardwaredylan-patel--x

9 Jul 2026

InferNet: Exploiting Aggregate GPU Profiles as Side-Channel for DNN Architecture Inference

arXiv:2304.03388v2 Announce Type: replace Abstract: Deep Neural Networks (DNNs) have become ubiquitous for their ability to solve problems across various domains, including computer vision, natural la

9 Jul 2026

Latency-Constrained DNN Architecture Learning for Edge Systems using Zerorized Batch Normalization

arXiv:2607.06922v1 Announce Type: cross Abstract: Deep learning applications have been widely adopted on edge devices, to mitigate the privacy and latency issues of accessing cloud servers. Deciding t

9 Jul 2026

C4N, now GA: Delivering cloud’s highest per vCPU network and block storage I/O for x86 workloads

As organizations scale modern workloads — from high-throughput databases and network/security appliances to real-time analytics and AI/ML inference — network and block storage performance can quickly

hardwaregoogle-cloud-ai

8 Jul 2026

A Multi-Task Deep Learning Framework for Real-Time Intelligent Video Surveillance with Temporal Event Validation

arXiv:2607.03131v1 Announce Type: cross Abstract: Modern video surveillance systems generate far more video streams than human operators can effectively monitor, making automated analysis essential fo

Generative wave propagator

arXiv:2607.04440v1 Announce Type: cross Abstract: Seismic wavefield simulation is fundamental to seismology, but conventional finite-difference (FD) methods remain limited by numerical dispersion and

HyperVAttention: Efficient Sparse Attention with Spatio-Temporal Clustering for Video Diffusion

arXiv:2607.03012v1 Announce Type: cross Abstract: Video Diffusion Transformers (VDiTs) have demonstrated significant capabilities in high-fidelity video generation. However, their ability to produce l

Scaling Weisfeiler-Leman Expressiveness Analysis to Massive Graphs with GPUs

arXiv:2607.02603v1 Announce Type: cross Abstract: The stable coloring of the Weisfeiler-Leman (1-WL) test is a cornerstone of Graph Neural Networks because it provides an upper bound to the expressive