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엔비디아, CUDA 6 출시…병렬 프로그래밍 간소화하고 성능 최대 8배 향상

JD 젤리비 편집국 · 2024.04.05 SHARE · COPY LINK

무슨 발표인가

  • CPU 라이브러리 교체로 애플리케이션 최대 8배 가속
  • Unified Memory로 CPU/GPU 메모리 관리 자동화
  • 8개 GPU까지 확장 시 9테라플롭스 이상

원문 (영어)

SANTA CLARA, CA -- NVIDIA today announced NVIDIA CUDA 6, the latest version of the world's most pervasive parallel computing platform and programming model. The CUDA 6 platform makes parallel programming easier than ever, enabling software developers to dramatically decrease the time and effort required to accelerate their scientific, engineering, enterprise and other applications with GPUs.

It offers new performance enhancements that enable developers to instantly accelerate applications up to 8X by simply replacing existing CPU-based libraries. Key features of CUDA 6 include: Unified Memory -- Simplifies programming by enabling applications to access CPU and GPU memory without the need to manually copy data from one to the other, and makes it easier to add support for GPU acceleration in a wide range of programming languages.

Drop-in Libraries -- Automatically accelerates applications' BLAS and FFTW calculations by up to 8X by simply replacing the existing CPU libraries with the GPU-accelerated equivalents. Multi-GPU Scaling -- Re-designed BLAS and FFT GPU libraries automatically scale performance across up to eight GPUs in a single node, delivering over nine teraflops of double precision performance per node, and supporting larger workloads than ever before (up to 512GB).

Multi-GPU scaling can also be used with the new BLAS drop-in library. "By automatically handling data management, Unified Memory enables us to quickly prototype kernels running on the GPU and reduces code complexity, cutting development time by up to 50 percent," said Rob Hoekstra, manager of Scalable Algorithms Department at Sandia National Laboratories.

"Having this capability will be very useful as we determine future programming model choices and port more sophisticated, larger codes to GPUs."

원문: NVIDIA News — "NVIDIA Dramatically Simplifies Parallel Programming With CUDA 6" (2024-04-05) 공식 원문: https://nvidianews.nvidia.com/news/nvidia-dramatically-simplifies-parallel-programming-with-cuda-6

#NVIDIA News
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엔비디아, CUDA 6 출시…병렬 프로그래밍 간소화하고 성능 최대 8배 향상

젤리비 편집국·2024.04.05·5 MIN
IN THIS PIECE
무슨 발표인가 원문 (영어)

무슨 발표인가

  • CPU 라이브러리 교체로 애플리케이션 최대 8배 가속
  • Unified Memory로 CPU/GPU 메모리 관리 자동화
  • 8개 GPU까지 확장 시 9테라플롭스 이상

원문 (영어)

SANTA CLARA, CA -- NVIDIA today announced NVIDIA CUDA 6, the latest version of the world's most pervasive parallel computing platform and programming model. The CUDA 6 platform makes parallel programming easier than ever, enabling software developers to dramatically decrease the time and effort required to accelerate their scientific, engineering, enterprise and other applications with GPUs.

It offers new performance enhancements that enable developers to instantly accelerate applications up to 8X by simply replacing existing CPU-based libraries. Key features of CUDA 6 include: Unified Memory -- Simplifies programming by enabling applications to access CPU and GPU memory without the need to manually copy data from one to the other, and makes it easier to add support for GPU acceleration in a wide range of programming languages.

Drop-in Libraries -- Automatically accelerates applications' BLAS and FFTW calculations by up to 8X by simply replacing the existing CPU libraries with the GPU-accelerated equivalents. Multi-GPU Scaling -- Re-designed BLAS and FFT GPU libraries automatically scale performance across up to eight GPUs in a single node, delivering over nine teraflops of double precision performance per node, and supporting larger workloads than ever before (up to 512GB).

Multi-GPU scaling can also be used with the new BLAS drop-in library. "By automatically handling data management, Unified Memory enables us to quickly prototype kernels running on the GPU and reduces code complexity, cutting development time by up to 50 percent," said Rob Hoekstra, manager of Scalable Algorithms Department at Sandia National Laboratories.

"Having this capability will be very useful as we determine future programming model choices and port more sophisticated, larger codes to GPUs."

원문: NVIDIA News — "NVIDIA Dramatically Simplifies Parallel Programming With CUDA 6" (2024-04-05) 공식 원문: https://nvidianews.nvidia.com/news/nvidia-dramatically-simplifies-parallel-programming-with-cuda-6

#NVIDIA News
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