Parallel Branch-and-Bound in multi-core multi-CPU multi-GPU heterogeneous environments
نویسندگان
چکیده
منابع مشابه
Device specialization in heterogeneous multi-GPU environments
In the last few years there have been many activities towards coupling CPUs and GPUs in order to get the most from CPU-GPU heterogeneous systems. One of the main problems that prevent these systems to be exploited in a device-aware manner is the CPU-GPU communication bottleneck, which often doesn’t allow to produce code more efficient than the GPU-only and the CPU-only counterparts. As a conseq...
متن کاملExecution of Compound Multi-Kernel OpenCL Computations in Multi-CPU/Multi-GPU Environments
Current computational systems are heterogeneous by nature, featuring a combination of CPUs and GPUs. As the latter are becoming an established platform for high-performance computing, the focus is shifting towards the seamless programming of these hybrid systems as a whole. The distinct nature of the architectural and execution models in place raises several challenges, as the best hardware con...
متن کاملpyPaSWAS: Python-based multi-core CPU and GPU sequence alignment
BACKGROUND Our previously published CUDA-only application PaSWAS for Smith-Waterman (SW) sequence alignment of any type of sequence on NVIDIA-based GPUs is platform-specific and therefore adopted less than could be. The OpenCL language is supported more widely and allows use on a variety of hardware platforms. Moreover, there is a need to promote the adoption of parallel computing in bioinforma...
متن کاملFast parallel genetic programming: multi-core CPU versus many-core GPU
Genetic Programming (GP) is a computationally intensive technique which is also highly parallel in nature. In recent years, significant performance improvements have been achieved over a standard GP CPU-based approach by harnessing the parallel computational power of many-core graphics cards which have hundreds of processing cores. This enables both fitness cases and candidate solutions to be e...
متن کاملMulti-level Parallel Query Execution Framework for CPU and GPU
Recent developments have shown that classic database query execution techniques, such as the iterator model, are no longer optimal to leverage the features of modern hardware architectures. This is especially true for massive parallel architectures, such as many-core processors and GPUs. Here, the processing of single tuples in one step is not enough work to utilize the hardware resources and t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Future Generation Computer Systems
سال: 2016
ISSN: 0167-739X
DOI: 10.1016/j.future.2015.10.009