Advances in GPU Research and Practice

<p>Part 1: Programming and Tools<br>1. Formal analysis techniques for reliable GPU programming: current solutions and call to action<br>2. SnuCL: A unified OpenCL framework for heterogeneous clusters<br>3. Thread communication and synchronization on massively parallel GPUs<br>4. Software-level task scheduling on GPUs<br>5. Data placement on GPUs</p> <p>Part 2: Algorithms and Applications<br>6. Biological sequence analysis on GPU<br>7. Graph algorithms on GPUs<br>8. GPU alignment of two and three sequences<br>9. Augmented Block Cimmino Distributed Algorithm for solving tridiagonal systems on GPU<br>10. GPU computing applied to linear and mixed-integer programming<br>11. GPU-accelerated shortest paths computations for planar graphs<br>12. GPU sorting algorithms<br>13. MPC: An effective floating-point compression algorithm for GPUs<br>14. Adaptive sparse matrix representation for efficient matrix-vector multiplication</p> <p>Part 3: Architecture and Performance<br>15. A framework for accelerating bottlenecks in GPU execution with assist warps<br>16. Accelerating GPU accelerators through neural algorithmic transformation<br>17. The need for heterogeneous network-on-chip architectures with GPGPUs: A case study with photonic interconnects<br>18. Accurately modeling GPGPU frequency scaling with the CRISP performance model</p> <p>Part 4: Power and Reliability<br>19. Energy and power considerations of GPUs<br>20. Architecting the last-level cache for GPUs using STT-MRAM nonvolatile memory<br>21. Power management of mobile GPUs<br>22. Advances in GPU reliability research<br>23. Addressing hardware reliability challenges in general-purpose GPUs</p>