CUDA-For-Clusters : A System for Efficient. Execution of CUDA Kernels on Multi-Core. Clusters. Raghu Prabhakar, R. Govindarajan, and Matthew J. Thazhuthaveetil.
Initial results on running several standard CUDA benchmark programs achieve impressive speedups of up to 7.5X on a cluster with 8 nodes, thereby opening up an�...
In this paper, we motivate and describe our initial study in exploring CUDA as a programming language for a cluster of multi-cores. We develop CUDA-For-Clusters�...
Aug 29, 2017 � I'm a researcher looking for examples of computations that spend a long time on the GPU, anything over 30 minutes for example.
Missing: Efficient | Show results with:Efficient
People also ask
What is CUDA How does CUDA utilize the parallel architecture of GPUs to achieve faster performance compared to traditional CPU based computing?
What are CUDA kernels?
What does CUDA stand for?
What is the difference between CUDA and GPU?
Mar 24, 2008 � MPI acts similar to a CUDA kernel, where you write one code and that same code is executed on every process. So you would need to do an if based�...
Missing: core | Show results with:core
Even though CUDA is driven by the GPU computing domain, we show that CUDA kernels can indeed be translated with FCUDA into efficient, customized multi-core�...
Jan 15, 2021 � I'm new to GPU programming, and I'm starting to get a bit confused, is it better to have large kernels or multiple smaller kernels?
Missing: System Execution
Sep 14, 2022 � Clusters enable multiple thread blocks running concurrently across multiple SMs to synchronize and collaboratively fetch and exchange data.
CUDA is a data parallel programming model that supports several key abstractions - thread blocks, hierarchical memory and bar- rier synchronization - for�...
Missing: Clusters: Clusters.
MCUDA [26] is a compiler that translates the CUDA kernels into a form suitable for efficient execution in multi-core CPUs. The kernel function is translated�...