算力商业
blogs.nvidia.com ·
@Timothy Costa
NVIDIA cuDSS 正式 GA，加速工程与科学仿真
NVIDIA 宣布 CUDA-X 库 cuDSS 正式可用，将大型稀疏线性系统求解迁移至 GPU，以缩短工程与科学仿真时间。官方称 Applied Materials 在 Ginestra 中实现最高 10 倍加速，Dassault Systèmes 的 Abaqus 报告 8-10 倍，ZEISS SMT 在 EUV 光刻等离子体仿真基准中测得 4 倍加速。cuDSS 支持 C、C++、Python、Fortran 接口，可从工作站扩展至集群，已被 COMSOL、Cadence、Siemens、Synopsys 等集成。
AI推荐理由 cuDSS 正式 GA 是明确的官方产品发布，正文给出 Applied Materials 最高 10 倍、Dassault Abaqus 8-10 倍、ZEISS SMT 4 倍等具体加速数据，并列出 COMSOL、Cadence、Siemens、Synopsys 等集成方，信息密度较高。局限是加速倍数均为厂商基准，缺少测试条件与基线细节，且属于 GPU 生态推广内容。
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NVIDIA cuDSS, launched today in general availability, is an NVIDIA CUDA-X library that shifts a critical part of engineering and scientific simulations onto GPUs.
Complex engineering feats — from advanced chips to aircraft to industrial systems —– depend on simulation to predict how designs will perform before they’re built. As designs become more complex, simulations take longer to run, increasing computing demands and limiting the number of ideas teams can test.
NVIDIA cuDSS accelerates solving large sparse systems — the math-heavy step that repeats throughout engineering and scientific simulations and often limits how many designs a team can test — by tapping into GPUs. This lets applications reduce time to results and increase simulation throughput, enabling end users to explore larger more realistic models, more accurate representations and a wider design space at a reduced cost.
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Industry leaders are already integrating NVIDIA cuDSS into their tools to transform workflows for their end customers:
Applied Materials: With cuDSS, Applied Materials accelerated sparse solves in Ginestra, its physics-based, defect-centric simulation platform, by up to 10x versus CPU-only approaches, speeding exploration of semiconductor materials and device reliability.
COMSOL: Using COMSOL Multiphysics with NVIDIA cuDSS on NVIDIA accelerated computing, ZEISS SMT achieved a measured 4x speedup in an EUV lithography plasma simulation benchmark, completing the full simulation in six days and 14 hours.
Cadence: Uses cuDSS in its Celsius software to accelerate simulations of heat, structural stress and warpage in advanced chips and 3D chip designs, helping customers including Nokia analyze complex designs faster.
Dassault Systèmes: Dassault Systèmes reports an 8-10x speedup using cuDSS within its Abaqus structural and computer simulation technology electromagnetic solvers for performance-critical simulations across industries.
Siemens: Siemens uses cuDSS in Simcenter STAR-CCM+ to accelerate simulations of structures in fluid-structure interaction workflows.
Synopsys: Synopsys uses cuDSS in its Sentaurus Device simulator tool to accelerate simulations of advanced logic, memory and power chips, helping Infineon model increasingly complex devices faster.
Accelerated Simulation at Scale
As simulation workloads grow in size and complexity, cuDSS can scale out of the box from individual workstations to large computing clusters.
Developers can integrate cuDSS into existing engineering, scientific and optimization software offerings, bringing GPU acceleration to tools already used by engineers and researchers. They can use cuDSS through C, C++, Python and Fortran interfaces.
Learn more about cuDSS by visiting the NVIDIA demo booth and Dassault Systèmes booth at GTC Berlin.
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