Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Operating systems, Package
Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Operating systems, Package, Task scheduling
Tags: Algorithms, Benchmarking, Computer science, nVidia, nVidia Quadro FX 3800, OpenCL, OpenMP, Operating systems, Performance
Tags: Computer science, CUDA, Heterogeneous systems, nVidia, Operating systems, Software Engineering, Tesla C2070
Tags: ATI, ATI Radeon HD 6970, Computer science, Heterogeneous systems, MPI, nVidia, nVidia GeForce GTX 480, OpenCL, Operating systems, Package
Tags: AES, ATI, ATI Radeon HD 6750 M, Computer science, nVidia, nVidia GeForce GTX 580, nVidia GeForce GTX 590, OpenCL, Operating systems, Security, Tesla M2070
Tags: Computer science, CUDA, Energy-efficient computing, nVidia, nVidia GeForce GTX 210, nVidia GeForce GTX 280, nVidia GeForce GTX 570, Operating systems, Task scheduling
Tags: Computer science, CUDA, Heterogeneous systems, nVidia, nVidia GeForce GTX 480, Operating systems, Package
Tags: Cloud, Computer science, GPU cluster, nVidia, nVidia GeForce GTX 480, OpenCL, Operating systems, Package
Tags: ATI, ATI Radeon HD 5870, Computer science, Heterogeneous systems, OpenCL, Operating systems, Package
Recent source codes
Most viewed papers (last 30 days)
- MusaCoder: Native GPU Kernel Generation with Full-Stack Training on Moore Threads GPU
- KForge: LLM-Driven Cross-Platform Kernel Generation for AI Accelerators
- Towards Feedback-to-Plan Decisions for Self-Evolving LLM Agents in CUDA Kernel Generation
- CodegenBench: Can LLMs Write Efficient Code Across Architectures?
- Autonomous heterogeneous catalyst discovery with a self-evolving multi-agent digital twin
- Leveraging AI Ecosystem for Portable and Sustainable GPU Kernels in HPC
- daVinci-kernel: Co-Evolving Skill Selection, Summarization, and Utilization via RL for GPU Kernel Optimization
- Tangram: Hiding GPU Heterogeneity for Efficient LLM Parallelization
- Fearless Concurrency on the GPU
- From Tokens to Regions: CUDA-Sensitive Instruction Tuning for GPU Kernel Generation




