Cover Image

The Art of Beating the Odds with Predictor-Guided Random Design Space Exploration

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Arnold, Felix, Bouvier, Maxence, Amaudruz, Ryan, Andri, Renzo, Cavigelli, Lukas
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Hardware Architecture
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

GENIAL: Generative Design Space Exploration via Network Inversion for Low Power Algorithmic Logic Units
by: Bouvier, Maxence, et al.
Published: (2025)

Explicit Sign-Magnitude Encoders Enable Power-Efficient Multipliers
by: Arnold, Felix, et al.
Published: (2025)

Stella Nera: A Differentiable Maddness-Based Hardware Accelerator for Efficient Approximate Matrix Multiplication
by: Schönleber, Jannis, et al.
Published: (2023)

Ara2: Exploring Single- and Multi-Core Vector Processing with an Efficient RVV 1.0 Compliant Open-Source Processor
by: Perotti, Matteo, et al.
Published: (2023)

A "New Ara" for Vector Computing: An Open Source Highly Efficient RISC-V V 1.0 Vector Processor Design
by: Perotti, Matteo, et al.
Published: (2022)

SoberDSE: Sample-Efficient Design Space Exploration via Learning-Based Algorithm Selection
by: Xu, Lei, et al.
Published: (2026)

Explainable Fuzzy Neural Network with Multi-Fidelity Reinforcement Learning for Micro-Architecture Design Space Exploration
by: Fan, Hanwei, et al.
Published: (2024)

Intelligent4DSE: Optimizing High-Level Synthesis Design Space Exploration with Graph Neural Networks and Large Language Models
by: Xu, Lei, et al.
Published: (2025)

CRADLE: Conversational RTL Design Space Exploration with LLM-based Multi-Agent Systems
by: Krupp, Lukas, et al.
Published: (2025)

AutoHLS: Learning to Accelerate Design Space Exploration for HLS Designs
by: Ahmed, Md Rubel, et al.
Published: (2024)

Multi-objective Optimization in CPU Design Space Exploration: Attention is All You Need
by: Xue, Runzhen, et al.
Published: (2024)

FlatAttention: Dataflow and Fabric Collectives Co-Optimization for Large Attention-Based Model Inference on Tile-Based Accelerators
by: Zhang, Chi, et al.
Published: (2026)

On Robustness and Generalization of ML-Based Congestion Predictors to Valid and Imperceptible Perturbations
by: Holtz, Chester, et al.
Published: (2024)

RL-MUL 2.0: Multiplier Design Optimization with Parallel Deep Reinforcement Learning and Space Reduction
by: Zuo, Dongsheng, et al.
Published: (2024)

Design Space Exploration of Approximate Computing Techniques with a Reinforcement Learning Approach
by: Saeedi, Sepide, et al.
Published: (2023)

ArtNet: Hierarchical Clustering-Based Artificial Netlist Generator for ML and DTCO Application
by: Kang, Andrew B. Kahng. Seokhyeong, et al.
Published: (2025)

Exploration of Low-Power Flexible Stress Monitoring Classifiers for Conformal Wearables
by: Afentaki, Florentia, et al.
Published: (2025)

JExplore: Design Space Exploration Tool for Nvidia Jetson Boards
by: Kutukcu, Basar, et al.
Published: (2025)

Exploration of Activation Fault Reliability in Quantized Systolic Array-Based DNN Accelerators
by: Taheri, Mahdi, et al.
Published: (2024)

From LLM to Silicon: RL-Driven ASIC Architecture Exploration for On-Device AI Inference
by: Ganti, Ravindra, et al.
Published: (2026)

MiCo: End-to-End Mixed Precision Neural Network Co-Exploration Framework for Edge AI
by: Jiang, Zijun, et al.
Published: (2025)

MPM-LLM4DSE: Reaching the Pareto Frontier in HLS with Multimodal Learning and LLM-Driven Exploration
by: Xu, Lei, et al.
Published: (2026)

Security Risks in Machining Process Monitoring: Sequence-to-Sequence Learning for Reconstruction of CNC Axis Positions
by: Krupp, Lukas, et al.
Published: (2026)

Learning Library Cell Representations in Vector Space
by: Liang, Rongjian, et al.
Published: (2025)

Design Space Exploration of DMA based Finer-Grain Compute Communication Overlap
by: Pal, Shagnik, et al.
Published: (2025)

AiEDA: An Open-Source AI-Aided Design Library for Design-to-Vector
by: Qiu, Yihang, et al.
Published: (2025)

PowerGenie: Analytically-Guided Evolutionary Discovery of Superior Reconfigurable Power Converters
by: Gao, Jian, et al.
Published: (2026)

iEEG Seizure Detection with a Sparse Hyperdimensional Computing Accelerator
by: Cuyckens, Stef, et al.
Published: (2025)

Exploring Quantization and Mapping Synergy in Hardware-Aware Deep Neural Network Accelerators
by: Klhufek, Jan, et al.
Published: (2024)

Deep Inverse Design for High-Level Synthesis
by: Chang, Ping, et al.
Published: (2024)

Designing Efficient LLM Accelerators for Edge Devices
by: Haris, Jude, et al.
Published: (2024)

Comprehensive Verilog Design Problems: A Next-Generation Benchmark Dataset for Evaluating Large Language Models and Agents on RTL Design and Verification
by: Pinckney, Nathaniel, et al.
Published: (2025)

PICBench: Benchmarking LLMs for Photonic Integrated Circuits Design
by: Wu, Yuchao, et al.
Published: (2025)

ShortCircuit: AlphaZero-Driven Circuit Design
by: Tsaras, Dimitrios, et al.
Published: (2024)

Evaluating Four FPGA-accelerated Space Use Cases based on Neural Network Algorithms for On-board Inference
by: Antunes, Pedro, et al.
Published: (2026)

TinyFormer: Efficient Transformer Design and Deployment on Tiny Devices
by: Yang, Jianlei, et al.
Published: (2023)

Architectural Implications of Neural Network Inference for High Data-Rate, Low-Latency Scientific Applications
by: Weng, Olivia, et al.
Published: (2024)

CIMFlow: An Integrated Framework for Systematic Design and Evaluation of Digital CIM Architectures
by: Qi, Yingjie, et al.
Published: (2025)

FedChip: Federated LLM for Artificial Intelligence Accelerator Chip Design
by: Nazzal, Mahmoud, et al.
Published: (2025)

QiMeng: Fully Automated Hardware and Software Design for Processor Chip
by: Zhang, Rui, et al.
Published: (2025)