oneAPI

Code Together is an interview series that explores challenges at the forefront of cross-architecture development, sponsored by Intel. We’ll talk with those across the industry who are forging a path on this often treacherous journey through an increasingly diverse, data-centric world. Join the conversation.

Jeff Hammond
Jeff Hammond
Principal Engineer, Intel

The oneAPI specification allows you to build standards-driven code, with a quicker path to performance, across CPUs, GPUs, FPGAs and other accelerators. It supports cross-architecture programming through a language, set of library APIs and a low-level hardware interface, as well as a reference stack. The specifications and source code are built on GitHub and integrate with upstream and downstream workflows. Intel Principal Engineer Jeff Hammond demonstrates how oneAPI works on a range of hardware and is built using GitHub. Contribute to the specification or the open source implementation. Use the base oneAPI software stack and port it to your favorite platform.

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Aksel Alpay
Jeff Hammond
Aksel Alpay
Engineer, Heidelberg University Computing Center
Jeff Hammond
Principal Engineer, Intel

Open standards underpin the future of heterogeneous programming, and as Intel Principal Engineer Jeff Hammond points out, SYCL has proven in many ways that “standards don’t cost you a thing and you get portability.” A modern C++ language, SYCL has demonstrated amazing growth and now boasts four implementations—ComputeCpp, triSYCL, hipSYCL and DPC++. hipSYCL Creator Aksel Alpay explains some of the differences between these implementations, and how hipSYCL is evolving to incorporate DPC++ features contributed to the SYCL 2020 specification, including unified shared memory (USM), reductions, group algorithms and subgroups. The two also dive into a discussion of buffers and accessors, and Aksel debunks a few myths around hipSYCL.

To learn more:

hipSYCL (GitHub)

Dive into DPC++ (Blog)

DPC++ Data Management across Multiple Architectures (Blog)

Data Parallel C++ Book

oneAPI

Penporn Koanantakool
AG Ramesh
Penporn Koanantakool
Senior Software Engineer, Google
AG Ramesh
Principal Engineer, Intel

Increased processing power, massive amounts of data, and the development of more advanced algorithms have brought deep learning to the forefront, and TensorFlow has emerged as one of the world’s most popular machine learning frameworks. Penporn Koanantakool, Google Senior Software Engineer, and Ramesh, Intel Principal Engineer, share how their teams are collaborating to optimize TensorFlow for the latest Intel technologies using oneAPI Deep Neural Network Library (oneDNN). The result: remarkable performance gains that will benefit applications spanning natural language processing, image and object recognition, autonomous vehicles, fraud detection, medical diagnosis and treatment, and much more. Intel-optimized TensorFlow is now made available through Intel® AI Analytics Toolkit and is being used within Google Cloud Platform and a Google Health project.

To learn more:

Intel® oneAPI Deep Neural Network Library

Intel® AI Analytics Toolkit

Accelerating DeepVariant with Intel’s AVX-512 Optimizations

TensorFlow-MKL int8 Optimizations for Cascade Lake

TensorFlow-MKL bfloat16 Optimizations for Cooper Lake

Andrew Lumsdaine
Chief Scientist, Northwest Institute for Advanced Computing
Mike Voss
Principal Engineer, Intel

Andrew Lumsdaine, Chief Scientist at Northwest Institute for Advanced Computing, shares his journey in parallelism, from the HPC community’s early skepticism of and eventual move to C++ to build large systems, to his pursuit to develop a series of C++ libraries to strike at the contradiction between abstraction and performance, to today’s reality that parallelism and heterogeneity are essential for achieving performance. Together, Andrew and Mike Voss, Principal Engineer at Intel, underscore the value of open standards and high-quality implementations of open standards—specifically, the oneAPI specification and Intel® oneAPI toolkits, respectively—and provide listeners with ways to get involved in helping shape ISO C++, Khronos SYCL, DPC++ and oneAPI.

To learn more:

Ricardo Menotti
oneAPI Developer Summit, Day 2 Tech talk 5

FPGAs have enormous potential to parallel many workloads, offering superior performance than other architectures for a fraction of the energy cost. However, designing custom architectures requires specific knowledge and is time consuming. Seismic applications for prospecting for oil and gas, which work based on the time it takes reflected sound waves to travel through materials of varying densities, are known for their complexity and high computational costs. In this lecture, we will report our experience in accelerating two of these applications using SYCL with oneAPI for FPGAs framework, as well as the results obtained so far.

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Xiaozhu Meng & Aaron Cherian
Xiaozhu Meng & Aaron Cherian
oneAPI Developer Summit, Day 2 Tech talk 4

HPC Kit is an integrated suite of tools for measurement and analysis of program performance on computers ranging from multicore desktop systems to the nation’s largest supercomputers. By using statistical sampling of timers and hardware performance counters, HPC Kit collects accurate measurements of a program’s work, resource consumption, and inefficiency and attributes them to the full calling context in which they occur. HPC Kit supports measurement and analysis of serial codes, threaded codes (e.g. pthreads, OpenMP), MPI, and hybrid (MPI+threads) parallel codes. With the prevalence of using GPU as an accelerator for scientific computation, we are extending HPC Kitto support applications accelerated with GPUs from several vendors. In this presentation, we are going to discuss our recent development for supporting Intel GPUs and our experience of profiling several applications porting to Intel GPUs using Data Parallel C++.

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Paul Navratil
oneAPI Developer Summit, Day 2 Lightning talks

Dr. Navratil will discuss the “state of the art” and near-term trends driving HPC application development efforts in preparation for the massive scale of data and computation in the ExaScale era. He will touch up the ongoing efforts of the SOLAR Ray Tracing Consortium’s efforts to utilize Ray Tracing for Compute and the role of the emerging ANARI Kronos API, the necessary merging of Compute and Visualization workflows, aka In Situ; plus advances in color theory enabling scientists to extract more detail during visual analysis.

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Raja Appuswamy
Raja Appuswamy
oneAPI Developer Summit, Day 2 Lightning talks

In the European Commission-funded Future and Emerging Technologies initiative OligoArchive, we are working on transforming DNA–the biological building block of life–into a digital building block for long-term data archival. One of the key steps in retrieving digital data stored in DNA involves clustering billions of strings with respect to edit distance. The computationally intensive nature of edit distance computation has made this step a critical bottleneck in the DNA data retrieval pipeline. In this talk, we will present project OneOligo—our scalable, hardware-accelerated solution for DNA read clustering. In doing so, we will first provide an overview the DNA data storage pipeline. Then, we will present OneJoin—a string-similarity join algorithm that synergistically combines algorithmic advances in low-distortion embedding with cross-architectural programming ability offered by DPC++, to scale-up clustering across CPUs and GPUs.

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Aleksandar Illic
oneAPI Developer Summit, Day 2 Tech talk 3

In the first part of this talk, we will introduce the Cache-aware Roofline Model (CARM) and expose its basic principles when modelling the performance upper-bounds of a processor. We will also discuss our recent research contributions in extending the model insightfulness with application-driven CARM, as well as applying the CARM principles to model power consumption and energy-efficiency upper-bounds. In the second part of this talk, we will rely on CARM implementation in Intel® Advisor to showcase its ability to drive the optimization of epistasis detection, an important application in bioinformatics. For both Intel CPU and GPU devices, we will demonstrate how CARM can be used to detect execution bottlenecks and provide useful hints on which type of optimizations to apply in order to fully exploit device capabilities. The guidelines provided by CARM were fundamental to achieve the speedups of more than 20x on Intel® six-core CPU and Gen 9.5 GPU.

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John Clyne
oneAPI Developer Summit, Day 2 Tech talk 2

VAPOR is the Visualization and Analysis Platform for Ocean, Atmosphere, and Solar Researchers. VAPOR provides an interactive 3D visualization environment that can also produce animations and still frame images. This talk will discuss the recent successful integration of Intel® oneAPI Rendering Toolkit and the benefits in performance, scalability, and high-fidelity Ray Tracing Visualization it provides.

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Hartwig Anzt
oneAPI Developer Summit, Day 2 Tech talk 2

In this talk, we will present the Ginkgo open source math library and its capabilities on Intel® GPU architectures. We will start with reporting our experiences in porting an NVIDIA-focused software stack to Intel’s DPC++ environment and the obstacles we encountered when using automated code conversion. We will then present the functionality Ginkgo currently provides for Intel GPUs, and present initial performance results.

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David Hardy
oneAPI Developer Summit, Day 1 Tech talk 5
Tareq Malas
oneAPI Developer Summit, Day 1 Tech talk 5

Molecular dynamics (MD) is an important computational methodology that can provide insight into the structure and function of sub-cellular assemblies of biomolecules at atomic level detail, accessing spatial and temporal resolutions that are not available to purely experimental approaches. As computational power has increased over the past several years, MD techniques have become an invaluable tool for tackling biomedically relevant challenges, such as improving our understanding of the molecular structure of the SARS-CoV-2 virus that causes COVID-19 and guiding computational approaches for screening candidate compounds as potential anti-viral drugs. NAMD is a parallel MD code designed for high-performance simulation of large biomolecular systems. It offers scalable performance on petascale class computers and has now for over ten years been a major application for the NSF supercomputing centers and for various DOE labs. One of the first exascale class computers will be the upcoming Aurora supercomputer based on the latest Intel GPU technology, making the adoption of oneAPI into NAMD critical for performance. In this presentation, we will discuss the ongoing NAMD development efforts of porting its many CUDA kernels to DPC++ with the Intel DPC++ Compatibility Tool and using the Intel® VTune™ Profiler to improve GPU utilization and overall performance of the new DPC++ kernels.

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Ho Leung Ng
oneAPI Developer Summit, Day 1 Tech talk 4

Computer-aided drug design uses chemistry simulations and calculations to accelerate the discovery of drug candidate molecules. Computational resources and time are cheap relative to the painstaking research in experimental laboratories. Recent advances in computing technologies and computational chemistry have greatly improved the accuracy and scope of computer-aided drug design, furthering the scientific appetite for computational power. Many scientific computing software tools are based on hand-crafted legacy code, written in Fortran for example, and have not been modernized for use on parallel architectures. The greatest challenge to improving software performance is that most developers and users of these tools are trained in the physical sciences with little formal background in software design. Software development tools must be easy to use for this user base.

We describe our efforts and successes using the Intel® oneAPI Math Kernel Library and Threading Building Blocks to improve the performance of computational drug design software. We describe the application of these tools by the Open Source COVID-19 drug discovery consortium and partnering scientists.

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Laura Cappelli
oneAPI Developer Summit, Day 1 Lightening talks

To fully exploit the physics reach of the High-Luminosity Large Hadron Collider, the LHC experiments are planning substantial upgrades of their detector technologies and increases of their data acquisition rates. The higher proton-proton interaction rate, pileup and event processing rate present an unprecedented challenge to the real-time and offline event reconstruction, requiring a processing power which is orders of magnitude larger than today, and exceeds by far the expected increase for conventional CPUs. The Compact Muon Solenoid (CMS) experiment is developing a fully heterogeneous reconstruction software that will be used during the next LHC data taking period, starting in 2022. Its first applications will be the online reconstruction running on a GPU-equipped High-Level Trigger (HLT) farm, and the offline reconstruction running on HPC centres worldwide. These activities will allow the collaboration to gain experience with parallel algorithms and a heterogeneous framework, that will be essential to leverage diverse kinds of accelerators during the HL-LHC data taking. To keep under control the cost of software development, maintenance and validation that this will entail, CMS is evaluating various performance portability frameworks that promise a “write once, run anywhere” approach, building the same code base for different back ends and accelerator types. The speaker will present the ongoing work to port the CMS reconstruction software to the Intel oneAPI platform and compare its performance on different back-ends with that of native code running on the same hardware.

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Data Parallel C++ (DPC++), the C++- and SYCL-based programming language of choice in the oneAPI programming environment, promises to have a single source code that addresses multiple hardware architectures. However, starting from scratch or rewriting existing application is tedious if not out of question in most cases. The Intel® oneAPI Compatibility Tool addresses this issue by assisting in the migration from CUDA to DPC++. In this talk, we share our experiences with migrating a typical CUDA stencil application code to DPC++ with the help of the tool. The presentation addresses the basic porting process, required manual steps, and issues we faced with the tsunami simulation easyWave. Besides these procedural steps, we point out performance numbers of the hardware devices supported by oneAPI and its evolving ecosystem. This is not limited to devices like Intel CPUs and GPUs but includes promising numbers for CUDA hardware as well. We also demonstrate what needs to be done to execute the migrated, CUDA-originated code on FPGAs.

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Alessandro Faria
oneAPI Developer Summit, Day 1 Lightening talks

In this talk we will look at oneVPL and how it is used in Certiface technology designed to combat fraud and protect honest people through the ability to differentiate between a live person and a recorded video. Certiface is based to harness heterogeneous computing architecture including CPUs and GPUs from servers to notebooks. The software tools such as oneVPL, computer vision techniques with OpenCV, OpenVINO and Deep Learning technologies based on Intel features such as Threading Building Blocks (TBB), Intel® Integrated Performance Primitives (Intel® IPP) and Intel® Math Kernel Library (Intel® MKL), and high-performance computing. This technology processes millions of faces per second in the cloud, making banking transaction operations in Brazil secure, fast and effective.

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Attila Krasznahorkay
oneAPI Developer Summit, Day 1 Lightening talks

The ATLAS Experiment is one of the general-purpose particle physics experiments built at the Large Hadron Collider at CERN, in Geneva, Switzerland. Its goal is to study the behavior of elementary particles at the highest energies ever produced in a laboratory, helping us better understand our universe.

The LHC, in what is called the High Luminosity LHC (HL-LHC), is going to increase the intensity of its particle beams many-fold over the next decade to allow us to study the rarest particle interactions possible. This increase in intensity will provide us with great challenges in analyzing the data collected from the ATLAS detector. To be able to process the data collected in that period, we will have to use novel data analysis techniques to cope with the increased complexity of our data.

In this presentation I will show results from a R&D project that implements parts of the charged particle track reconstruction code of ATLAS using oneAPI/DPC++. Allowing us to offload parts of the necessary calculations to different accelerators, providing us with a sizable processing speed increase for data that we expect to collect during the HL-LHC data taking.

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Denisa Constantinescu
Denisa Constantinescu
oneAPI Developer Summit, Day 1 Tech talk 3
Professor Rafael Asenjo
oneAPI Developer Summit, Day 1 Tech talk 3

Our goal is to make it easy and feasible to implement solutions for autonomous decision-making and planning under uncertainty on low-power mobile platforms. We focus on practical applications, such as autonomous driving and service robotics, that must run on SoC mobile platforms. These applications often have real-time execution constraints. The main challenge is to keep the runtime and energy performance in check while making it easy for the users (programmers) to write their code to solve decision-making problems.

Our proposal involves using low-power heterogeneous computing strategies, sparse data structures to fit large real-world decision-making problems on SoCs with scarce memory and computing resources, and oneAPI with DPC++ programming. We compare three heterogeneous scheduling strategies implemented with OpenCLTM + Threading Building Blocks (TBB) versus oneAPI + TBB (oneTBB) to run parallel code on CPU-GPU SoCs and evaluate their performance on a set of benchmarks for planning for mobile robot navigation. The benchmarks compute an optimal navigation plan with Value Iteration (VI) algorithm. VI is a fundamental method to find optimal policies, allowing an intelligent agent to act autonomously in environments where the effects of its actions are not deterministic. The experiments show that the implementations based on DPC++ are up to five times easier to program while incurring only three to eight percent overhead.

This work’s main novelty is solving large-scale Markov Decision Processes on low-power heterogeneous CPU-GPU platforms and demonstrating that we can achieve both performance and productivity when the scheduling strategy is carefully selected. We remark that the oneAPI programming model creates new opportunities to improve performance and efficiency in low-power systems.”

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Ahmed Ayyad
oneAPI Developer Summit, Day 1 Tech talk 1

As a leading company in the seismic imaging domain, we require our software products to be as highly performant, efficient and sustainable as possible. The state-of-the-art hardware architecture is constantly changing which can be very challenging for software engineers to adapt to these changes, which requires either writing several variants of the software or shifting from one accelerator to another depending on the current norm.

Using oneAPI as a unified programming model for our Reverse Time Migration (RTM) software accelerated our development efforts on multiple hardware platforms. This reduced our need for variant coding as we now use the same code base for any hardware accelerator and gave us the advantage of working on a variety of processor platforms, avoiding being locked into a single vendor.

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Xinmin Tian
oneAPI Developer Summit, Day 2 Tech talk 1

In the high-performance computing realm, the emerging DPC++/SYCL programming model is getting attention while OpenMP* continues to be the popular parallel programming model to a wide range of HPC/AI accelerators such as Xe GPUs and FPGAs. This presentation includes:

  • A brief overview of the DPC++ and OpenMP offloading Models
  • An overview of Intel’s LLVM compiler technology for DPC++ and OpenMP offloading
  • A deep dive on performance tuning for one AI workload on Intel CPU and Xe GPU

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Erik Lindahl
Erik Lindahl
oneAPI Developer Summit, Day 2 Keynote

GROMACS is a state-of-the-art computational tool to understand the molecular mechanisms of the protein molecules in our cells. Eric’s lab leads the development of the GROMACS molecular dynamics toolkit, which is one of the world’s most widely used HPC applications, and which has been tuned to achieve outstanding performance and scaling on everything from laptops to supercomputers and even the Playstation as part of Folding@Home. His team is among the ones that have been able to fully exploit both CPU and GPU hardware from every vendor available. In this talk he will talk about his Lab’s experience with oneAPI and how it has helped them expand GROMACS’s support of heterogenous hardware.

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Andrew Richards
Andrew Richards
oneAPI Developer Summit, Day 1 Tech talk 1

In the world of AI & HPC programming, to get high performance, developers need accelerators that have high levels of parallelism, but often these uses closed and proprietary programming models.

Developers are demanding open and standards-based solutions that deliver both performance and portability. An open and unified programming model gives developers a way to cost-effectively take advantage of the growing diversity of processor platforms and avoid being locked into a single vendor. This presentation will explore where we are in creating an open ecosystem that uses open standards and how we can get the industry to work together with open standards. Codeplay has been working on these challenges for years having been closely involved in the OpenCL and SYCL Khronos standards for parallel compute. Most recently we have been involved in oneAPI spec definition and expanding DPC++, adding support for Nvidia GPUs.

I will show the vast progress that has been made today, where we’re going next and how you can help us build an open ecosystem for AI and HPC programming.

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Joe Curley
oneAPI Developer Summit, Day 1 Keynote

The need to analyze increasingly complex datasets is driving demand for dedicated workload accelerator chips to be installed in data center servers to complement the main server processor. Intel’s solution is oneAPI, a project to deliver a unified software development environment across CPU and accelerator architectures. oneAPI is an Industry Initiative – based on standards, open specification and includes a unified language & libraries that deliver full native code performance. In this Keynote Joe will give a flavor of why Intel started this initiative and the plans going forward. He will recognize the Dev community for the excellent work they have done this past year with oneAPI and give a taste to the audience why you should care about listening to them talk about their “oneAPI experiences” over a period of the next two days.

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Denisa Constantinescu
Maura Tokay
Denisa Constantinescu
PhD student in mechatronics and Researcher in the Computer Architecture Department, University of Malaga
Maura Tokay
Computer scientist and lead software programmer at Science Systems and Applications, Inc., and recent Master’s graduate at the University of Maryland Baltimore County (UMBC)

Denisa Constantinescu, a PhD student in Mechatronics, and a researcher in the Computer Architecture Department at the University of Malaga, and Maura Tokay, a lead software programmer at Science Systems and Applications, Inc., and a computer scientist within the Department of Agriculture, share how their work is helping advance the fields of robotics, economics, manufacturing, agriculture and more, supported by oneAPI and the Intel DevCloud. They inspire us with glimpses of their journeys into tech, and what they’re looking forward to.

Tom Deakin
James Brodman
Tom Deakin
Senior Research Associate and Lecturer, High-Performance Computing Research Group, University of Bristol
Dr. James Brodman
Software Engineer, Intel

Dr. Tom Deakin, senior research associate and lecturer in the High-Performance Computing Research Group at the University of Bristol, and Dr. James Brodman, software engineer at Intel, unpack the tricky topic of performance portability to reveal what this concept truly means and ways to achieve it. As contributors to the Khronos SYCL Working Group—from the user and implementer perspectives—they talk about the exciting growth of the SYCL community, marked, in part, by its implementations that now support a variety of hardware architectures, including DPC++ and hipSYCL.

Senior HPC Engineer, Megware Computer
Technical, Enterprise and Cloud Segment Marketing Manager, Intel

As high performance computing (HPC) moves far beyond its traditional users to the domains of AI, machine learning, enterprises and the cloud, and heterogeneous programming becomes the norm, Nico Mittenzwey, senior HPC engineer at Megware Computer, and Mike Lee, technical, enterprise and cloud segment marketing manager at Intel, discuss the considerations in optimizing HPC clusters and applications. Nico explains how the Intel MPI Library has helped Megware and its customers rise to these challenges, providing real-world examples of two of the company’s most recent projects. He also explores the challenges of fragmentation in heterogeneous computing environments, and how a single, common programming model can help address these challenges.

To learn more:

Alex Baden
David Petersohn
Technical Director, OmniSci
Machine Learning Engineer, Intel

Data scientists spend 60% of their time cleaning and preprocessing data, transforming this dirty data into crystallized insights. Dataframes, such as Pandas, provide exceptional tooling to address data wrangling tasks, yet Pandas themselves increasingly lack ease and speed as they scale. Alex Baden, Technical Director at OmniSci, and Devin Petersohn, Machine Learning Engineer at Intel, dive into the challenges and considerations of dataframe scaling. They explore how the Intel Modin / OmniSci solution, part of the Intel AI Analytics Toolkit, offers an open road to quick, transparent scaling across heterogeneous architectures. They also explain how this solution’s integration with the rest of the Python ecosystem enables data scientists to focus on extracting value from data rather than provisioning and orchestrating resources.

Max Liani
Alex Wells
Max Liani
Senior Lead Engineer of RenderMan, Pixar Animation Studios
Alex Wells
Principal Engineer, Intel

To deliver increasingly captivating stories in the world of animated movies takes passion and determination. The passion to continually push the boundaries of what’s possible. The determination to continually seek ways to make technology easily approachable by artists, so that the artists can focus on what they’re best at—telling stories that capture our imaginations. Max Liani , Senior Lead Engineer of RenderMan at Pixar Animation Studios, and Alex Wells, Principal Engineer at Intel, talk about collaborating to push the boundaries of what’s possible at the intersection of technology and art, and the ramifications that pervade outside the realm of motion pictures.

Ruyman Reyes
Stuart Adams
Ruyman Reyes
Software Engineer, Codeplay Software
Stuart Adams
Software Engineer, Codeplay Software

DPC++ provide developers with the ability to write standard C++ code for heterogeneous systems, and accelerate execution using a range of different processors including CPUs, GPUs and FPGAs.

Software developers can use this implementation to target Nvidia GPUs using any SYCL code, without any porting or special tricks required. If you have existing SYCL code, or if you are writing new SYCL code, you can compile it and target Nvidia GPUs without modifications.

Doing a hands-on exercise will help you to learn how to invoke the compiler to compile your code for Nvidia hardware using DPC++.

Erik Lindahl
Roland Schulz
Biophysics Professor, Stockholm University & KTH Royal Institute of Technology
Parallel Software Engineer, Intel

In Part I of two episodes about GROMACS, one of the world’s most widely used open source molecular dynamics (MD) applications, Erik Lindahl, Biophysics Professor at Stockholm University & KTH Royal Institute of Technology, and Roland Schulz, Parallel Software Engineer at Intel, unpack the mysteries of MD. As Erik explains, MD helps us understand “everything from the proteins inside our bodies to the largest galaxies in the world.” Erik and Roland discuss MD simulation using GROMACS, the immense benefits and challenges it brings, its role in the fight against our global pandemic, and some of the most promising developments. They also explore the significance of the Folding@home project as it relates to the world’s supercomputers and exascale computing.

Krystian Ligenza
Mike Voss
Krystian Ligenza
Software Architect, Autodesk
Mike Voss
Principal Engineer, Intel

Krystian Ligenza, Autodesk Maya Software Architect, and Mike Voss, Intel Principal Engineer, talk about how the need for immersive experiences in VFX and 3D animated movies and games has driven the need for increasingly more capable (and complex) software and hardware. They discuss how Autodesk and Intel are addressing these challenges, and explain how the companies are collaborating to equip the most iconic animation studios and game developers with the tools needed to deliver ultra-realistic, award-winning entertainment experiences.

Andrew Richards
Hal Finkel
Andrew Richards
CEO, Codeplay Software
Hal Finkel
Lead for Compiler Technology and Programming Languages, Argonne National Lab

Is oneAPI living up to its promise? How do oneAPI and DPC++ relate to the Khronos Group SYCL and ISO C++ standards? Andrew Richards and Hal Finkel respond to these provocative questions and more from Sanjiv Shah, Intel GM and VP of Developer Software Engineering. They share their experiences with oneAPI and DPC++, and talk about oneAPI’s best aspects and what they would like to change about this cross-architecture programming model. Listen in.

Jeff Hammond
Ronan Keryell
Principal Engineer, Intel
Principal Software Engineer, Xilinx

Ronan Keryell and Jeff Hammond explain why open collaboration — modeled through open source and open standards — is key to solving some of today’s biggest challenges in research and industry, revealing some of the misconceptions, or least understood aspects, along the way. Then they explore the value of open languages and programming models, diving into ISO C++, Khronos Group SYCL, the amazing SYCL community, and what excites them most about the SYCL 2020 Provisional Specification.

AI Solutions Engineer, Intel
CEO and Co-Founder, Anaconda

Peter Wang explains the series of happy accidents that have led to organic adoption of Python as the number one language among developers in data science and machine learning in this episode of Code Together. He and David Liu talk about the latest advancements in hardware and software and how to make them more accessible to developers, as well as how to bridge the multiple layers of abstraction. They also explore collaboration on building a low-power, high-performance data science stack, democratization of data literacy, and the future of Python in this action-packed discussion between two data science experts.

Julia Sukharina
Mehdi Goli
Senior Engineering Manager, Intel
Principal Software Engineer, Codeplay Software

Existing math kernel libraries have lacked portability across heterogeneous platforms—until now. A unifying programming model—and availability of standard library interfaces—enables development of performance-portable libraries among diverse hardware architectures. In this episode, we talk about a collaborative project to make this portability possible, and dive into Mehdi’s work to enable the first math library implementation for oneAPI on Nvidia GPUs.

Geoff Lowney
Andrew Richards
Senior Fellow, Intel
CEO, Codeplay Software

Geoff and Andrew discuss the value of standards in enabling hardware and software developers to collaborate and innovate. From the early days of video games to modern AI, Andrew weaves an unexpected yet common thread between these, and explore how oneAPI builds on this foundation. Andrew talks about Codeplay’s contributions to oneAPI, focused on enabling development on Nvidia GPUs, while Geoff shares his vision of enabling broad data parallelism and portability across platforms, to provide a glimpse into what’s next for oneAPI.

Alice Chang
Hal Finkel
Vice President and General Manager of Compiler Engineering, Intel
Lead for Compiler Technology and Programming Languages, Argonne National Lab

In this episode of Code Together, we talk about how the industry is uniting to address the need for programming portability and performance across diverse architectures- particularly important with the rise of data-intensive workloads like AI and machine learning. We discuss the shift to modern C++ programming models and how the cross-industry oneAPI initiative and DPC++, bring much-needed portable performance to developers.

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