Sun 14 Apr 2019 16:50 - 17:15 at Garden Room - Session3

By utilizing diverse heterogeneous hardware resources, developers can significantly improve the performance of their applications. Currently, in order to determine which parts of an application suit a particular type of hardware accelerator better, an offline analysis that uses a priori knowledge of the target hardware configuration is necessary. To make matters worse, the above process has to be repeated every time the application or the hardware configuration changes.

This paper introduces TornadoVM, a virtual machine capable of reconfiguring applications, at runtime, for hardware acceleration based on the currently available hardware resources. Through TornadoVM, we introduce a new level of compilation in which applications can benefit from heterogeneous hardware. We showcase the capabilities of TornadoVM by executing a complex computer vision application and six
benchmarks on a heterogeneous system that includes a CPU, an FPGA, and a GPU. Our evaluation shows that by using dynamic reconfiguration, we achieve an average of 7.7× speedup over the statically-configured accelerated code.

Sun 14 Apr
Times are displayed in time zone: (GMT-04:00) Eastern Time (US & Canada) change

16:00 - 18:05: Research Papers - Session3 at Garden Room
vee-2019-papers16:00 - 16:25
Thomas ShullUniversity of Illinois at Urbana-Champaign, Jian HuangUniversity of Illinois at Urbana-Champaign, Josep TorrellasUniversity of Illinois at Urbana-Champaign
vee-2019-papers16:25 - 16:50
Wenzhi CuiGoogle, Daniel RichinsThe University of Texas at Austin, Yuhao ZhuUniversity of Rochester, Vijay Janapa ReddiHarvard University
vee-2019-papers16:50 - 17:15
Juan FumeroUniversity of Manchester, UK, Michail PapadimitriouUniversity of Manchester, UK, Foivos S. ZakkakUniversity of Manchester, UK, Maria XekalakiUniversity of Manchester, UK, James ClarksonUniversity of Manchester, UK, Christos KotselidisUniversity of Manchester, UK
DOI Authorizer link
vee-2019-papers17:15 - 17:40
Dongyang WangUniversity of Science and Technology of China, China, Binzhang FuHuawei Technologies, n.n., Gang LuHuawei Technologies, n.n., Kun TanHuawei Technologies, n.n., Bei HuaHuawei Technologies, n.n. / University of Science and Technology of China, China
vee-2019-papers17:40 - 18:05
Li LiuGeorge Mason University, USA, Haoliang WangAdobe Research, USA, An WangCase Western Reserve University, USA, Mengbai XiaoOhio State University, USA, Yue ChengGeorge Mason University, USA, Songqing ChenGeorge Mason University, USA