… , we design a massively multi-threaded GPU-based grid file for static, … grid file variant to
handle data skews efficiently. Our implementations on the NVIDIA G80 GTX graphics card are …

… 2.1 GPGPU A Graphics Processing Unit was extended to the generalpurpose high-performance
computing area after the emergence of General Purpose GPU (GPGPU) under certain …

… Our comprehensive evaluation using three different grid sizes with six … GPUs using CUDA.
In Proceedings of 2nd workshop on general purpose processing on graphics processing …

… of in-memory libraries between CPUs and GPUs. We found that GPU is mostly not supported
by the current in-memory … interconnects, eg, NVLink, between GPUs, we believe this will an …

… To validate this bottleneck, we conduct a detailed profiling of representative image processing
… To overcome the bottleneck of memory bandwidth, the 3Dstacking processing-in-memory (…

… as both a programmable graphics processor and a scalable … of result data grids, partitioning
each result grid into coarse-… , and 3D texture arrays in memory via the texture subsystem. …

… Grid already had a parallel for construct used to target OpenMP threaded loops on multicore
… ” transformation is needed in data arrays in memory. However they semantically differ in the …

… Grid already had a parallel for construct used to target OpenMP threaded loops on multicore
… ” transformation is needed in data arrays in memory. However they semantically differ in the …

… A thread block has a block ID within its grid. A grid is an array of thread blocks that execute
… The content of resister which needs to be stored in memory is loaded into DM_Write signal …

… of workloads that can benefit from in-memory computation have very simple parallelism
and … in-memory commands. Further, the tDFG is a unified abstraction for near-data and inmemory…