论文标题
将库达迁移到oneapi：史密斯 - 水手案例研究
Migrating CUDA to oneAPI: A Smith-Waterman Case Study
论文作者
论文摘要
为了面对与异质计算相关的编程挑战，英特尔最近引入了ONEAPI，这是一个新的编程环境，允许在数据并行C ++（DPC ++）语言中开发代码，并在CPU，GPU，GPU，FPGAS等不同设备上运行。为了解决基于CUDA的遗产代码，Oneapi提供了一种兼容性工具（DPCT），可促进向DPC ++的迁移。由于在生物信息学上下文中有大量现有的基于CUDA的软件，因此本文使用DPCT介绍了我们的经验移植SW＃DB（一种众所周知的序列对齐工具）。从实验工作中，可以证明DPCT对SW＃DB代码迁移的有用性和迁移的DPC ++代码的跨GPU供应商的跨架构可移植性。此外，性能结果表明，迁移的DPC ++代码报告与其CUDA本地的效率率相似，甚至在某些测试中甚至更好（大约+5％）。
To face the programming challenges related to heterogeneous computing, Intel recently introduced oneAPI, a new programming environment that allows code developed in Data Parallel C++ (DPC++) language to be run on different devices such as CPUs, GPUs, FPGAs, among others. To tackle CUDA-based legacy codes, oneAPI provides a compatibility tool (dpct) that facilitates the migration to DPC++. Due to the large amount of existing CUDA-based software in the bioinformatics context, this paper presents our experiences porting SW#db, a well-known sequence alignment tool, to DPC++ using dpct. From the experimental work, it was possible to prove the usefulness of dpct for SW#db code migration and the cross-GPU vendor, cross-architecture portability of the migrated DPC++ code. In addition, the performance results showed that the migrated DPC++ code reports similar efficiency rates to its CUDA-native counterpart or even better in some tests (approximately +5%).
