Table of Contents

并行计算

CUDA、OpenMP、OpenACC

和并行计算相关的基础知识：并行计算

论文阅读

  1. A compression-based memory-efficient optimization for out-of-core GPU stencil computation
  2. A Compute Unified System Architecture for Graphics Clusters Incorporating Data-Locality
  3. A Device‑Side Execution Model for Multi‑GPU Task Graphs
  4. A Method for Estimating Task Granularity for Automating GPU Cycle Sharing
  5. A Performance Model for Evaluating Inter-Node Device-Side Communication
  6. Accelerating GPU-Based Out-of-Core Stencil Computation with On-the-Fly Compression
  7. Automated Code Generation of High-Order Stencils for a Dataflow Architecture
  8. DCUDA Dynamic GPU Scheduling with Live Migration Support
  9. GPUサイクル共有システムにおける分散深層学習の高速化
  10. Lightning Scaling the GPU Programming Model Beyond a Single GPU
  11. Multi‑GPU work sharing in a task‑based dataflow programming model
  12. PACC An Extension of OpenACC for Pipelined Processing of Large Data on a GPU
  13. PaRSEC Parallel Runtime Scheduling and Execution Controller
  14. STAPL standard template adaptive parallel library
  15. Towards Automating Multi-dimensional Data Decomposition for Executing a Single-GPU Code on a Multi-GPU System
  16. GPU上のアウトオブコア・ステンシル計算を高速化するための実行パラメータの選定
  17. 単一GPUコードをマルチGPU環境で実行するための多次元データ分割手法の検討

期刊、会议：

  1. Future Generation Computer Systems (FGCS)

适合并行计算的任务