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High-Level Synthesis
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이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Embedded FPGA Acceleration of Brain-Like Neural Networks: Online Learning to Scalable Inference
iDSE: Navigating Design Space Exploration in High-Level Synthesis Using LLMs
LLM-DSE: Searching Accelerator Parameters with LLM Agents
Intelligent4DSE: Optimizing High-Level Synthesis Design Space Exploration with Graph Neural Networks and Large Language Models
HLS-Eval: A Benchmark and Framework for Evaluating LLMs on High-Level Synthesis Design Tasks
Design and Implementation of an FPGA-Based Hardware Accelerator for Transformer
Can Reasoning Models Reason about Hardware? An Agentic HLS Perspective
A Reconfigurable Stream-Based FPGA Accelerator for Bayesian Confidence Propagation Neural Networks
Exploring Code Language Models for Automated HLS-based Hardware Generation: Benchmark, Infrastructure and Analysis
MetaML-Pro: Cross-Stage Design Flow Automation for Efficient Deep Learning Acceleration
Neural Architecture Codesign for Fast Physics Applications
Intelligent experiments through real-time AI: Fast Data Processing and Autonomous Detector Control for sPHENIX and future EIC detectors
Agentic-HLS: An agentic reasoning based high-level synthesis system using large language models (AI for EDA workshop 2024)
KALAM: toolKit for Automating high-Level synthesis of Analog computing systeMs
Hierarchical Mixture of Experts: Generalizable Learning for High-Level Synthesis
Learning to Compare Hardware Designs for High-Level Synthesis
Are LLMs Any Good for High-Level Synthesis?
Efficient Task Transfer for HLS DSE
rule4ml: An Open-Source Tool for Resource Utilization and Latency Estimation for ML Models on FPGA
HENNC: Hardware Engine for Artificial Neural Network-based Chaotic Oscillators
Exploring the Limitations of Kolmogorov-Arnold Networks in Classification: Insights to Software Training and Hardware Implementation
Deep Inverse Design for High-Level Synthesis
Automated C/C++ Program Repair for High-Level Synthesis via Large Language Models
New Solutions on LLM Acceleration, Optimization, and Application
Cross-Modality Program Representation Learning for Electronic Design Automation with High-Level Synthesis
fSEAD: a Composable FPGA-based Streaming Ensemble Anomaly Detection Library
SynthAI: A Multi Agent Generative AI Framework for Automated Modular HLS Design Generation
Fast Algorithms for Spiking Neural Network Simulation with FPGAs
HLSFactory: A Framework Empowering High-Level Synthesis Datasets for Machine Learning and Beyond
HLSTransform: Energy-Efficient Llama 2 Inference on FPGAs Via High Level Synthesis
Skip the Benchmark: Generating System-Level High-Level Synthesis Data using Generative Machine Learning
Allo: A Programming Model for Composable Accelerator Design
AutoHLS: Learning to Accelerate Design Space Exploration for HLS Designs
Subgraph Extraction-based Feedback-guided Iterative Scheduling for HLS
Hierarchical Source-to-Post-Route QoR Prediction in High-Level Synthesis with GNNs
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.