Steve Forde is responsible for Adobe's visual effects product line, including Adobe After Effects (Ae) in Creative Suite 6, which offers a new GPU-accelerated 3D ray-traced compositing workflow capability. This enables motion graphics artists to quickly design realistic geometric text and shapes directly in a 3D space, eliminating the traditional, time-consuming need for external 3D tools. Steve says: "We created an environment in conjunction with NVIDIA that allows motion designers to quickly create high-fidelity motion graphics inside Ae -- without the computational expense -- by fully utilizing the GPU. This allows for much greater creativity while still being able to make the deadline."

Vladimir "Vlado" Koylazov is co-founder and head of software development at Chaos Group, the makers of V-Ray and V-Ray RT. Chaos Group was founded in 1997 in Bulgaria. The company's interactive ray tracing software, V-Ray RT, leverages GPUs and CUDA to create photorealistic computer-generated imagery in real time. "Our software is used by artists to create so many amazing things. Whether it's a new electric vehicle, an energy efficient building or a blockbuster film, we're providing the tools to help artists visualize their imaginative designs," says Vlado.

Paulo Souza is the lead HPC (high-performance computing) developer of seismic imaging codes at Petrobras, the Brazilian multinational energy company. Paulo started working with GPUs in 2006, when he ported seismic applications to CUDA. Paulo comments: "We've invested in five GPU clusters, including the Grifo04 built with Tesla M2050 GPUs. Grifo04 is the fastest supercomputer in Latin America." At SC12 in November, Petrobras received the 2012 HPCwire Readers' Choice Award for Best Use of HPC in the Oil and Gas Industry.

Mark is the CEO of Colorfront, a digital post production facility which he co-founded in 2000 with his brother Aron. The Colorfront On-Set Dailies system was used by EFILM on the set of the new James Bond movie, Skyfall. Mark comments: "Colorfront On-Set Dailies relies exclusively on GPU image processing in CUDA. We can take advantage of multiple GPUs for even higher performance." NVIDIA GPUs drive Colorfront products on a range of platforms, from the Retina MacBook Pro through the Mac Pro, and up to the HP Z820 with multiple GPUs to process 4K RAW files at over 100 FPS.

Brian is a senior engineer in the signal processing and communications group at MathWorks, a leading developer of technical computing software. MathWorks is most well-known for the MATLAB and Simulink products. Brian is the primary developer of the GPU support for toolboxes in the signal processing area. He says: "We want to put the benefits of GPU computing into the hands of domain experts."

Anders Eklund is a postdoc at the Virginia Tech Carilion Research Institute. He conducts research in the field of medical image processing, especially fMRI (functional magnetic resonance imaging). Anders utilizes the CUDA programming model and and runs his calculations through MATLAB.

Erik Lindahl of KTH Royal Institute of Technology and Stockholm University is a project leader for GROMACS, the popular open-source molecular dynamics program. The next release of GROMACS will include strong CUDA support. "CUDA is a long-term stable development that we can trust," comments Erik.

Supratik Moulik is the founder of Triradiate Industries, a software development firm. "GPUs provide a way for complex visualization and analysis tasks to be performed quickly and with easily-attainable hardware," he says. "This translates into faster and more readily-available diagnostic tools which allow doctors to spend more time on patient care."

Michael Bussmann leads a Junior Research Group at HZDR in Dresden, Germany. His research focuses on computational radiation physics for applications in areas such as radiation therapy. "With GPU computing we have seen dramatic speed up of our code, which for the first time allows us to have live simulations of realistic scenarios," he says. His team's projects include PIConGPU, one of the world's fastest particle-in-cell codes.

Pete Willemsen, Associate Professor at the University of Minnesota Duluth, is using GPU computing to better understand complex interactions between urban areas and the environment. "Through the use of GPU-based simulation we hypothesize that there are urban structures and well-placed green infrastructure that can help to minimize energy use while also minimizing air pollution exposure. We hope our results can help guide future green urban planning projects," says Pete.

Lorena Barba, assistant professor at Boston University, is a computational scientist and fluid dynamicist. A strong advocate of GPU computing, she teaches a computational fluid dynamics course that focuses on interactive collaboration rather than in-class lectures. She says: "GPUs are without a doubt a disruptive technology in the world of high-performance computing."

Princeton's Iain Couzin is an expert in the study of collective animal behavior. His lab uses experimental systems - from ants and locust swarms to schooling fish and even human crowds - to explore the fundamental principles that underlie collective behavior. "GPU computing has utterly transformed the science we can do," he says.

William Putman, research meteorologist, aims to maximize the impact of satellite observations in climate, weather and atmospheric composition prediction using comprehensive global models and data assimilation. Using GPU acceleration and CUDA, his goal is to improve the throughput for the intermediate resolution models used in climate prediction and assessments.

Denis Bastieri leads the Fermi Large Area Telescope (LAT) team, which observes and analyzes high-energy gamma rays from galaxies, black holes, pulsars and supernovae. Providing computational capabilities at one tenth the cost of conventional systems, CUDA GPUs allow him to accelerate his research and reduce the raw data coming from the satellite (around 120 GB/day) into meaningful physical information.

According to HP Labs' Ren Wu, CUDA is a "game-changer" that enables the rapid analysis of massive volumes of business intelligence data. Using GPUs to accelerate big data analytics on multiple scales, HP Labs has achieved a 5-20x performance advantage over a pure CPU approach. GPUs will enable Ren Wu to gain new insights in the understanding of a number of critical areas, such as the environment, human health and global financial systems.

Postdoc Fellow Joshua Adelman is harnessing the computational power of CUDA GPUs to better understand and treat diseases, including ALS, epilepsy and Type 2 diabetes. Using molecular dynamics, Adelman is simulating transport proteins that may hold the key to the development of new and more effective treatments. GPU acceleration has provided a several hundred-fold increase in protein simulation throughput.

Virginia Tech is the inaugural research partner for the NVIDIA Foundation's Compute the Cure initiative. Team leader Wu-Chun Feng comments: "We plan to use the award to fundamentally change the way cancer biologists conduct their science....Supercomputing is no longer just the domain of big-iron supercomputers but also of personal desktop or deskside supercomputers. The domain area that I can foresee really benefiting the most from heterogeneous computing is the area of personalized medicine, which tailors healthcare to individual patients."

Ross Walker developed AMBER, a molecular dynamics (MD) software package for the simulation of biomolecules. Simulations help bio-physicists and computational chemists drive scientific discovery, such as creating more effective drugs to treat a range of diseases, e.g., the H1N1 virus. With GPU acceleration, AMBER is helping researchers dramatically speed up the process of developing better treatments.

Biophotonics leverages optics/light to enhance research in medicine and the life sciences. Today, histological analysis with microscopy is a primary methodology for cancer diagnosis. However, it can be difficult to identify the type of cancer. CUDA GPUs enable Alexander Doronin to accelerate simulations by 1000x and to accelerate new biophotonics techniques.

Anders Eklund specializes in medical image processing. His area of interest is functional magnetic resonance imaging (fMRI), which identifies brain activity from magnetic resonance images as a means to identify and treat a variety of brain afflictions. Eklund has deployed GPU computing to save five years of processing time during the development and testing of a new algorithm for non-parametric statistical analysis of fMRI data.

Jesse Rosenzweig and his team at Elemental Technologies have developed high-performance video algorithms for heterogeneous GPU/CPU architectures. Elemental integrates CUDA GPUs to decompress, process and recompress content in the video processing pipeline. The resulting system allows media companies to deliver high-quality video streams of live events, satellite feeds, sports and more to TVs, PCs, tablets, and other mobile devices in real-time.

Allan P. Engsig-Karup and researchers at the Technical University of Denmark (DTU) are focused on estimating the flow kinematics and design loads on ocean structures, such as ships, oil platforms, energy devices, where predictions are required for the maximum expected lifetime load. The team has achieved impressive scalability results for the GPU-accelerated implementation of its OceanWave3D wave simulation model.

Bart Gallet is researching improvements for the efficiency and safety of air transportation. The design of airspace and traffic flows is based on manual processes, as custom computer systems typically required to process the vast amounts of data are too expensive. However, CUDA and GPUs provide a cost-effective solution, speeding up key airspace and traffic flow computations 14 times faster.

Dr. Monish Tandale is leveraging the power of GPUs to improve the efficiency and safety of the U.S. air traffic system. He says: "With increasing computational capability available at our disposal, we can develop and analyze highly complex traffic flow models and run optimization algorithms to generate optimal schedules and routing of aircraft. The goal is to use automation to allow more people to fly without being inconvenienced by congestion and delayed flights."

Dr. Jeffrey Vetter manages The Keeneland Project, a National Science Foundation (NSF)-funded program that provides a high performance computing system for the open science community. According to Vetter, "CUDA is a phenomenon" so pervasive that it is allowing large numbers of scientists and students to harness the power of GPU computing to accelerate a range of advanced research projects.

Dr. Mehdi Raessi's research is focused on multi-phase flows and free-surface flows with phase change, which aims to identify more-efficient, environmentally friendly energy devices. GPU-based systems enable Dr. Raessi and his team to study much larger problems at a level of detail that was not feasible before.

Dr. Vincent Natoli develops and ports high performance technical applications for some of the biggest corporations in the world, primarily oil and gas companies. With GPUs, Dr. Natoli and his customers are seeing application acceleration of up to 20x compared with CPU-only systems, as well as cost savings due to the reduction of infrastructure footprint and power consumption.

Dr. Axel Kohlmeyer focuses on molecular dynamics (MD) and visualization research. GPUs and CUDA have enabled the processing of large, complex research calculations that was impossible just a short time ago, spawning a new wave of creativity in the study of compound systems, such as large bio-molecules embedded into realistic environments such as membranes.

John Humphrey is a pioneer in GPU computing and inventor of the CULA GPU-accelerated linear algebra library. EM Photonics' customers include the U.S. Navy, which relies on sophisticated CFD (computational fluid dynamics) modeling to simulate landings and takeoffs based on variables such as light conditions, weather and approach angles. GPUs help decrease simulation time by an order of magnitude as compared to conventional systems.

While Kang Zhang was a PhD candidate at Johns Hopkins University, he used CUDA GPUs for research in interventional Optical Coherence Tomography (OCT) for microsurgery. OCT is an imaging modality capable of non-invasive 3D micrometer-resolution imaging, which makes it highly suitable for guiding microsurgery. Kang developed an ultra-high-speed, real-time imaging system using a hardware-software platform based on GPU technology.

Vitaliy Lomakin and his team at the University of California, San Diego (UCSD) develop simulators for computational electromagnetics and micromagnetics that are essential in the design of components such as solar cells, radar and antennas and hard drives. GPU-based simulators have a significant predictive power that allows analysis, design, and validation of systems before and during fabrication of products.

Veteran technology inventor Stephen Fried is the founder of Microway. Microway's solutions include WhisperStation-PSC and fully-integrated Tesla GPU-based clusters, which are used by scientists for a variety of applications, from designing aircraft and space vehicles to mapping the ocean floor. BioStack-LS, a CUDA/Tesla-based Microway product, is pre-configured for life sciences software, including AMBER and MATLAB.

André R. Brodtkorb is a research scientist at SINTEF in Norway, where he works on GPU acceleration and algorithm design for shallow water simulations, tsunami warnings and simulation of storm surges and dam breaks. GPU-based systems allow SINTEF to run simulations at higher resolutions.

PhD student Martin Peniak is creating robots that can develop cognitive capabilities through interaction with their environments. Martin is using a CUDA-enabled software called Aquila to develop complex artificial neural networks for the real-time control of the robot as part of iTalk (Integration of Action and Language in Humanoid Robots), which is his PhD thesis project.

Doug Miles and his team at PGI create software tools to maximize performance and portability of applications across Linux, Windows and OSX. The partnership of PGI and NVIDIA has offered flexible tools to developers, including CUDA Fortran and the PGI CUDA C compiler. Doug comments: Today's application developers need flexibility. They want to be able to create innovative apps that leverage parallel computing and then deploy these apps on a wide range of target systems."

Arnaud Mazurier of ERM and Francois Curnier of Digisens utilized CUDA technology for data reconstruction of newly-discovered ancient organisms in Gabon, Africa. A team of scientists used GPU-based computed tomography to reconstruct data more quickly (6-10 minutes with GPUs versus 12-15 hours on CPUs).

Ben Jiang, CEO of Nexiwave, is using the power of GPUs to improve speech indexing for easy extraction of archived content. "Ninety percent of human communication is through speech," he explains. "The amount of spoken words that could potentially be indexed and searched is staggering." Speech indexing can be efficiently processed in parallel which means the GPU is a perfect fit for it.