PDF-CUDA Creatures

Andrew HershbergerVadim OgievetskyJuly 17th 2010 m 1 w 1 m 2 w 2 m n w n Random 01 w r Constant 1 w c Sameness11 w s In 1981 Axelrod and Hamilton examined the iterated Prisoners Dilemma It. heterogeneous programming. Katia Oleinik. koleinik@bu.edu. Scientific Computing and Visualization. Boston . University. Architecture. NVIDIA Tesla M2070: . Core clock: 1.15GHz . Single instruction . 448 CUDA cores . . Acknowledgement: the lecture materials are based on the materials in NVIDIA teaching center CUDA course materials, including materials from Wisconsin (. Negrut. ), North Carolina Charlotte (. Wikinson. ITS Research Computing. Mark Reed . Objectives. Learn why computing with accelerators is important. Understand accelerator hardware. Learn what types of problems are suitable for accelerators. Survey the programming models available. CUDA Simulation. Benjy. Kessler. Given a brittle substance with a crack in it.. The goal is to study how the crack propagates in the substance as a function of time.. This accomplished by simulating the substance as a grid of points with forces acting upon them.. GPGPU Programming in CUDA. Supada . Laosooksathit. NVIDIA Hardware Architecture. Host. memory. Recall. 5 steps for CUDA Programming. Initialize device. Allocate. device memory. Copy. data to device memory. About An Incredible Species That Can Survive The Most Perilous . Environments. Introduction. Tardigrades- amazing creatures. They can survive extreme habitats that would cause humans and other animals to die a very painful death, some of them even beyond Earth. Never more than 0.5 mm long, these creatures did what 6 ft tall humans could never accomplish- they can be brought back to life! As BBC explains, it’s not how these creatures can survive and why, the question is, why have we never evolved to do the same. They can survive space, extreme heat, extreme cold, large amounts of radiation, great amounts of geological pressure, and without water. Turns out, other creatures can do some of these things, but all of them?- doubtful. This ancient species has been able to do what we never could… . NVIDIA Corporation. Tesla GPU Computing. A Revolution in High Performance Computing. Agenda. CUDA Review. Architecture. Programming Model. Memory Model. CUDA C. CUDA General Optimizations. Fermi. Next Generation Architecture. © Dan Negrut, . 2012. UW-Madison. Dan Negrut. Simulation-Based Engineering Lab. Wisconsin Applied Computing Center. Department of Mechanical Engineering. Department of . Electrical and Computer Engineering. CUDA Lecture 7. CUDA Threads and Atomics. The Problem: how do you do global communication?. Finish a kernel and start a new one. All writes from all threads complete before a kernel finishes. Would need to decompose kernels into before and after parts. Performance considerations. (CUDA best practices) . NVIDIA CUDA C programming best practices guide. ACK: CUDA teaching center Stanford (. Hoberrock. and . Tarjan. ).. Outline. Host to device memory transfer. Håkon Kvale . Stensland. Simula Research Laboratory. PC Graphics Timeline. Challenges. :. Render infinitely complex scenes. And extremely high resolution. In 1/60. th. of one second (60 frames per second). on . Ubuntu. Cuda. download site. . https://developer.nvidia.com/cuda-downloads. $ . sudo. . dpkg. -. i. cuda-repo-ubuntu1404_7.5-18_amd64.deb . $ . sudo. apt-get update . $ . sudo. apt-get install . introduce the use of multiple CUDA streams to overlap memory transfers with kernel computations.. Also introduced is paged-locked memory. 2. Page-locked host memory. (also called pinned host memory). Cliff Woolley NVIDIADeveloper Technology GroupGPUCPUGPGPU Revolutionizes ComputingLatency Processor Throughput processorLow Latency or High ThroughputCPUOptimized for low-latency access to cached dat