Posts in Ecosystems and Partners

Introducing AMD’s Next-Gen Fortran Compiler

We are excited to share a brief preview of AMD’s Next-Gen Fortran Compiler, our new open source Fortran complier supporting OpenMP offloading. AMD’s Next-Gen Fortran Compiler is a downstream flavor of LLVM Flang, optimized for AMD GPUs. Our Next-Gen Fortran Compiler enables OpenMP offloading and offers a direct interface to ROCm and HIP. In this blog post you will:

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Stone Ridge Expands Reservoir Simulation Options with AMD Instinct™ Accelerators

Stone Ridge Technology (SRT) pioneered the use of GPUs for high performance reservoir simulation (HPC) nearly a decade ago with ECHELON, its flagship software product. ECHELON, the first of its kind, engineered from the outset to harness the full potential of massively parallel GPUs, stands apart in the industry for its power, efficiency, and accuracy. Now, ECHELON has added support for AMDInstinct accelerators into its simulation engine, offering new flexibility and optionality to its clients.

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Siemens taps AMD Instinct™ GPUs to expand high-performance hardware options for Simcenter STAR-CCM+

Siemens recently announced that its Simcenter STAR-CCM+ multi-physics computational fluid dynamics (CFD) software now supports AMD Instinct™ GPUs for GPU-native computation. This move addresses its users’ needs for computational efficiency, reduced simulation costs and energy usage, and greater hardware choice.

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AMD Collaboration with the University of Michigan offers High Performance Open-Source Solutions to the Bioinformatics Community

Long read DNA sequencing technology is revolutionizing genetic diagnostics and precision medicine by helping us discover structural variants and assemble whole genomes. It also helps us study evolutionary relationships. Lower sequencing costs and high-throughput portable long read sequencers are revolutionizing precision medicine today. Long read sequencers from the top manufacturers including Oxford Nanopore (ONT) and PacBio, can produce reads that are much longer than previous generations of sequencers. However, long reads vary in length and are significantly more error prone than short reads. Sequence alignment (on CPUs) is one of the main bottlenecks in long read processing workflows.

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Programming AMD GPUs with Julia

Julia is a high-level, general-purpose dynamic programming language that automatically compiles to efficient native code via LLVM, and supports multiple platforms. With LLVM, comes the support for programming GPUs, including AMD GPUs.

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