Today, the OpenPOWER Foundation announced the lineup of speakers for the OpenPOWER Summit 2016, taking place April 5-8 at NVIDIA’s GPU Technology Conference (GTC) at the San Jose Convention Center. The Summit will bring together dozens of technology leaders from the OpenPOWER Foundation to showcase the latest advancements in the OpenPOWER ecosystem, including collaborative hardware, software and application developments – all designed to revolutionize the data center.
Registration is now open for the 2016 OpenPOWER Summit, which will take place April 5-7 in San Jose, California in conjunction with the GPU Technology Conference. With a conference theme of “Revolutionizing the Datacenter,” the event has issued its Call for Speakers and Exhibits.
“This talk will introduce these three debugging techniques and provide some suggestions on selecting the optimal approach for a variety of debugging scenarios such as hangs, numerical errors, and crashes. Specific examples will be given using the TotalView debugger but the concepts covered may apply to other debugging tools such as GDB and the NVIDIA NSIGHT debugger.”
In this video from the GPU Technology Conference, Saber Feki from KAUST and Ahmed Al-Jarro from Fujitsu Labs in Europe present: Experiences in Porting Scientific Applications to GPUs Using OpenACC.
In this video, Aaron Vose from Cray presents: Porting Computational Physics Applications to the Titan Supercomputer with OpenACC and OpenMP.
“Learn how we achieve great GPU performance with an auto-tuned sparse matrix multiplication library, enabling quantum simulation of millions of electrons.”
“OpenACC and OpenMP provide programmers with two good options for portable, high-level parallel programming for GPUs. This talk will discuss similarities and differences between the two specifications in terms of programmability, portability, and performance.”
“Learn about extensions that enable efficient use of Partitioned Global Address Space (PGAS) Models like OpenSHMEM and UPC on supercomputing clusters with NVIDIA GPUs. PGAS models are gaining attention for providing shared memory abstractions that make it easy to develop applications with dynamic and irregular communication patterns. However, the existing UPC and OpenSHMEM standards do not allow communication calls to be made directly on GPU device memory. This talk discusses simple extensions to the OpenSHMEM and UPC models to address this issue.”
“We present a state-of-the-art image recognition system, Deep Image, developed using end-to-end deep learning. The key components are a custom-built supercomputer dedicated to deep learning, a highly optimized parallel algorithm using new strategies for data partitioning and communication, larger deep neural network models, novel data augmentation approaches, and usage of multi-scale high-resolution images.”
“We present results for a platform consisting of an NVM Express SSD, a CAPI accelerator card and a software stack running on a Power8 system. We show how the threading of the Power8 CPU can be used to move data from the SSD to the CAPI card at very high speeds and implement accelerator functions inside the CAPI card that can process the data at these speeds.”