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cuZK: Accelerating Zero-Knowledge Proof with A Faster Parallel Multi-Scalar Multiplication Algorithm on GPUs

Tao Lu, Chengkun Wei, Ruijing Yu, Yi Chen, Li Wang, Chaochao Chen, Zeke Wang, and Wenzhi Chen

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Tags: Algorithms, Benchmarking, Computer science, CUDA, Elliptic curves, Machine learning, nVidia, nVidia GeForce GTX 3060, Security, Tesla V100

October 9, 2022 by hgpu

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

UniCoder: Unified Visual-to-Code Generation via Symbolic Rewards and Reference-Guided Code Optimization

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

CuFuzz: An API-Knowledge-Graph Coverage-Driven Fuzzing Framework for CUDA Libraries

AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning

AutoPass: Evidence-Guided LLM Agents for Compiler Performance Tuning

Probe-and-Refine Tuning of Repository Guidance for AI Coding Agents

Probe-and-Refine Tuning of Repository Guidance for Coding Agents

CUDAnalyst (CUDA + Analyst)

Towards Feedback-to-Plan Decisions for Self-Evolving LLM Agents in CUDA Kernel Generation

CodegenBench

CodegenBench: Can LLMs Write Efficient Code Across Architectures?

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

KernelBenchX: A Comprehensive Benchmark for Evaluating LLM-Generated GPU Kernels

CUDA Kernel Fusion Benchmarks

Analyzing the Impact of Kernel Fusion on GPU Tensor Operation Performance: A Systematic Performance Study

IntelliKit: Agent-first tooling for AMD hardware

Kerncap: Automated Kernel Extraction and Isolation for AMD GPUs

DITRON: Distributed Compiler based on Triton for Parallel Systems

DITRON: Distributed Multi-level Tiling Compiler for Parallel Tensor Programs

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