惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
L
LangChain Blog
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
Recent Announcements
Recent Announcements
大猫的无限游戏
大猫的无限游戏
罗磊的独立博客
MongoDB | Blog
MongoDB | Blog
博客园 - 【当耐特】
博客园 - 叶小钗
I
InfoQ
MyScale Blog
MyScale Blog
H
Help Net Security
月光博客
月光博客
Vercel News
Vercel News
B
Blog
酷 壳 – CoolShell
酷 壳 – CoolShell
D
DataBreaches.Net
Cyber Security Advisories - MS-ISAC
Cyber Security Advisories - MS-ISAC
N
Netflix TechBlog - Medium
宝玉的分享
宝玉的分享
WordPress大学
WordPress大学
GbyAI
GbyAI
Blog — PlanetScale
Blog — PlanetScale
博客园 - Franky

cs.DC updates on arXiv.org

DUAL-BLADE: Dual-Path NVMe-Direct KV-Cache Offloading for Edge LLM Inference Progressive Semantic Communication for Efficient Edge-Cloud Vision-Language Models Efficient, VRAM-Constrained xLM Inference on Clients Folding Tensor and Sequence Parallelism for Memory-Efficient Transformer Training & Inference DORA: A Scalable Asynchronous Reinforcement Learning System for Language Model Training AMMA: A Multi-Chiplet Memory-Centric Architecture for Low-Latency 1M Context Attention Serving RaMP: Runtime-Aware Megakernel Polymorphism for Mixture-of-Experts Spark Policy Toolkit: Semantic Contracts and Scalable Execution for Policy Learning in Spark Internet of Everything in the 6G Era: Paradigms, Enablers, Potentials and Future Directions PolyKV: A Shared Asymmetrically-Compressed KV Cache Pool for Multi-Agent LLM Inference A Survey on Split Learning for LLM Fine-Tuning: Models, Systems, and Privacy Optimizations ITAS: A Multi-Agent Architecture for LLM-Based Intelligent Tutoring Latency and Cost of Multi-Agent Intelligent Tutoring at Scale TACO: Efficient Communication Compression of Intermediate Tensors for Scalable Tensor-Parallel LLM Training FreeScale: Distributed Training for Sequence Recommendation Models with Minimal Scaling Cost CommFuse: Hiding Tail Latency via Communication Decomposition and Fusion for Distributed LLM Training A Taxonomy and Resolution Strategy for Client-Level Disagreements in Federated Learning Usable Agent Discovery for Decentralized AI Systems Cloud to Edge: Benchmarking LLM Inference On Hardware-Accelerated Single-Board Computers Data-Free Contribution Estimation in Federated Learning using Gradient von Neumann Entropy Shard the Gradient, Scale the Model: Serverless Federated Aggregation via Gradient Partitioning Promoting Simple Agents: Ensemble Methods for Event-Log Prediction GraphLeap: Decoupling Graph Construction and Convolution for Vision GNN Acceleration on FPGA AGNT2: Autonomous Agent Economies on Interaction-Optimized Layer 2 Infrastructure FedSIR: Spectral Client Identification and Relabeling for Federated Learning with Noisy Labels Stream-CQSA: Avoiding Out-of-Memory in Attention Computation via Flexible Workload Scheduling A Delta-Aware Orchestration Framework for Scalable Multi-Agent Edge Computing Federated Learning over Blockchain-Enabled Cloud Infrastructure Optimal Routing for Federated Learning over Dynamic Satellite Networks: Tractable or Not? Sherpa.ai Privacy-Preserving Multi-Party Entity Alignment without Intersection Disclosure for Noisy Identifiers
EURETILE 2010-2012 summary: first three years of activity...
Pier Stanislao Paolucci, Iuliana Bacivarov, Gert Goossens, Raine · 2013-05-07 · via cs.DC updates on arXiv.org

This is the summary of first three years of activity of the EURETILE FP7 project 247846. EURETILE investigates and implements brain-inspired and fault-tolerant foundational innovations to the system architecture of massively parallel tiled computer architectures and the corresponding programming paradigm. The execution targets are a many-tile HW platform, and a many-tile simulator. A set of SW process - HW tile mapping candidates is generated by the holistic SW tool-chain using a combination of analytic and bio-inspired methods. The Hardware dependent Software is then generated, providing OS services with maximum efficiency/minimal overhead. The many-tile simulator collects profiling data, closing the loop of the SW tool chain. Fine-grain parallelism inside processes is exploited by optimized intra-tile compilation techniques, but the project focus is above the level of the elementary tile. The elementary HW tile is a multi-processor, which includes a fault tolerant Distributed Network Processor (for inter-tile communication) and ASIP accelerators. Furthermore, EURETILE investigates and implements the innovations for equipping the elementary HW tile with high-bandwidth, low-latency brain-like inter-tile communication emulating 3 levels of connection hierarchy, namely neural columns, cortical areas and cortex, and develops a dedicated cortical simulation benchmark: DPSNN-STDP (Distributed Polychronous Spiking Neural Net with synaptic Spiking Time Dependent Plasticity). EURETILE leverages on the multi-tile HW paradigm and SW tool-chain developed by the FET-ACA SHAPES Integrated Project (2006-2009).