Surface reconstruction is an important trend in 3D scanning. The problem is to recreate surfaces from a given point cloud within the shortest possible time and with a given quality criteria. There is a set of different approaches for solving this problem, which includes Self-Organized Maps, Bayesian reconstruction and Poisson reconstruction.
ARACHNE: A neural-neuroglial network builder with remotely controlled parallel computing
Here we put forward a newly developed simulation environment ARACHNE: it enables an investigator to build and explore cellular networks of arbitrary biophysical and architectural complexity using the logic of NEURON and a simple interface on a local computer or a mobile device.
Good (and Bad) Reasons to Outsource Software Engineering
Software outsourcing is a fairly common business practice these days. Although “outsourcing” may just mean asking somebody "outside" of the company to perform the work, it typically means that work is "shipped" off-shore.
Adaptation of Image Processing Software for Windows Azure and HPC Cluster
In parallel computing systems computations are executed simultaneously, wholly or in part. This approach is based on the partitioning of a big task into smaller subtasks that can run in parallel.
Parallel computing techniques in CAD drawing analysis
Sketches obtained as a result of import or export from different CAD packages to DXF/DWG formats often contain broken geometry relations: broken tangent, broken horizontal or vertical relations, gaps between entities, etc.
Comparison of ConcRT, OpenMP and TBB technologies for multi-core numeric computation
In order to compare ConcRT, OpenMP and TBB technologies, we implemented a few algorithms from different areas of numeric computation and compared their performance with C++ equivalents. Four functions were implemented.
Mathematical modeling of complex problems is far more mainstream than it once was, and Excel has played a major role in making that happen. From linear programming to statistical models, Excel is used to implement many different modeling techniques. Built-in functions and custom worksheets significantly enhance Excel’s flexibility and suitability as the modeling tool of choice within existing customer-based applications.
Advantages of the distributed implementation of the Monte Carlo method in neurobiology simulation
The goal of this paper is to demonstrate the performance benefits from using distributed algorithms and computational power of clusters for Monte Carlo method in simulating processes in the field of neurobiology.
Microsoft announced new technology for GPGPU called C++ Accelerated Massive Parallelism - C++ AMP. It accelerates the execution of C++ code by taking advantage of the GPUs present on video cards with DirectX11 support. The main structure of C++ AMP is influenced by its main competitors like OpenCL and CUDA. But unlike OpenCL and CUDA, that are more oriented in C code, C++ AMP looks like STL library with new C++11 support.
As a software provider, you are undoubtedly stressed. You need high quality developers but can't spend a fortune and have little time to babysit anyone. Perhaps you considered outsourcing– but you probably also have heard many horror stories in the media and from colleagues. We actually agree, typical outsourcing is not usually the answer as it’s proven to fail often. Thus, after more than 10 years providing successful outsourcing solutions, we at AMC Bridge decided to share our experiences. Here are top 5 tips we have used to ensure that outsourcing works properly.
Engineering and manufacturing organizations continue to face challenges when managing large repositories of 3D models, including manual shape comparison, inconsistent similarity assessments, and the time‑consuming navigation of extensive part libraries. Traditional CAD search and manual similarity methods rely heavily on metadata, naming conventions, or subjective human judgment—approaches that do not scale and often produce inconsistent results.
AMC Bridge’s latest technology demonstration, Similar Parts Search, explores how combining artificial intelligence (AI) with advanced 3D geometric processing can address these challenges and significantly improve the discovery, reuse, and evaluation of structurally similar parts across engineering workflows. By leveraging learned geometric representations of 3D models, the POC enables consistent, geometry‑aware similarity detection across large repositories, independent of how parts are named or categorized.
When the founders of AMC Bridge formed our company a quarter century ago, we wanted to help clients with digital transformation – but we realized that technical know-how alone wasn’t enough. We had to develop a deep understanding of our customers – their ambitions, their competition, their existential challenges. What we’ve learned from hundreds of clients while engineering their software ecosystems holds true across enterprises. To move decisively, modern organizations need a secure, open platform that connects data, automates high-value work, and gives stakeholders clear, current context for their next moves.
As engineering software evolves toward increasingly complex, connected, and computation‑heavy workflows, development teams face a pressing challenge: how to build 3D solutions that remain robust, interoperable, and scalable today and in the future.
Addressing this challenge, Siemens Digital Industries Software and AMC Bridge co‑hosted the live webinar "Unlock Next Generation 3D Software: Getting Started with Parasolid," offering a deep look into how Parasolid empowers modern 3D applications and how AMC Bridge helps companies implement it successfully.
As software vendors modernize their 3D platforms, transitioning to a reliable and widely adopted geometry kernel becomes essential for improving modeling accuracy, streamlining development, and accelerating innovation. To support organizations on this journey, Siemens Digital Industries Software and AMC Bridge hosted a joint webinar focused on Parasolid implementation. Discover how vendors can speed up product development by leveraging a PLM Components–based ecosystem and collaborating with engineering teams experienced in advanced geometry workflows.
