GPU Computing, formerly GPGPU, is a technique of using the GPUs for computing, which allows for both substantially higher performance and increased power efficiency compared to CPUs. The two main frame works used in the field of GPU Computing are Nvidia's CUDA and the OpenCL (Open Computing Language) standard, both of which we employ.

HPC has developed Xtream CUDA C++ framework for developer productivity.

Research Posters and Sessions

GPU computing for embedded applications presented at a session on embedded GPU computing at the Royal Institute of Technology (KTH) in Stockholm. In the talk we share some of our experiences in using GPU:s for radar signal and image processing applications in the embedded space, with particular focus on the Tegra K1 and Tegra X1 processors.

Enabling Real-Time Cancer Research Tool presented at the GPU Technology Conference (GTC) 2014 in San José. The video and PDF of the session is now up and can be found here and here.

Optimization Opportunities and Pitfalls when Implementing High Performance 2D Convolutions presented at GTC 2014 in San José. The video and PDF of the session is now up and can be found here and here.

Optimized LU-decomposition with Full Pivot for Small Batched Matrices presented at the GTC 2013 in San José. The video and PDF of the session is now up and can be found here and here.

High performance sorting using CUDA capable GPUs, the fastest sorting implementation on any existing general-purpose architecture, presented at GTC 2013 in San José.

CUDA-based LU Factorization with pivoting for 10,000s of small dense matrices vs. Intel MKL, presented at GTC San José 2012.

Actual power consumption in Pattern Matching on CUDA GPUs, presented at GTC Asia 2011.

Testimonials from clients

HPC was the sole solutions provider for developing our Gradientech Tracking Tool. The high quality of the end-product means scientist now have an excellent software tool for analyzing chemotactic cell-responses in areas such as cancer research.

Sara Thorslund, CEO, Gradientech

HPC was a key contributor to our new real-time video enhancement product for interventional radiology. In medical devices, performance and reliability are of paramount importance and HPC helped us reach our goals with their deep GPGPU expertise, great team skills, and their dedication to our success. We look forward to future collaborations with HPC.

Arto Järvinen, R&D Director, ContextVision

HPC's contributions to our LDI 5s Data Path software meant we didn't just reach our performance goals, we exceeded them. Their input on GPU programming in particular had a significant impact on our product‘s compute performance. I strongly recommend employing HPC for any performance oriented software development.

Anders Österberg, Expert, Innovation Field High Performance Computing, Micronic Mydata