Author Archives: Georgios Keramidas

Think Silicon @ Synopsys ARC Processor Summit Beijing

Think Silicon with great pleasure participated in the Synopsys ARC Processor Summit Beijing held on Wednesday, 15 November 2017 in Beijing, China.
The prototype, which was created by Think Silicon and Synopsys, of an ultra-low power Internet of Things (IoT) platform designed for connected wearable, mobile, and embedded display devices was showcased at this event. The prototype combines the best of Synopsys® technology sporting a DesignWare® ARC EM5D Processor with Think Silicon® products including NEMA®|p, NEMA®|DC, and NEMA®|GFX-API, resulting in a developer solution aimed at ultra-low power connected wearables and low-power embedded applications. Both companies have tools to assist developers in creating world-class products for a wide variety of markets. The Power Models of NEMA® GPUs (part of the NEMA® SW toolchain) were developed as part of the LPGPU2 EU-funded project.
Also, Dr. Iakovos Stamoulis, CTO at Think Silicon, made a presentation titled “Ultra-low Power 3D Micro-GPU for IoT-Class Devices” addressing how the emerging Internet of Things (IoT) market adds design challenges for engineers while discussing how the NEMA® Series of ultra-low power micro-GPU cores bridges this gap.

Think Silicon @ the Linley Processor Conference 2017

Think Silicon successfully participated last week in the Linley Processor Conference 2017 which was held between 4-5 October at California, U.S.. As being the largest and most prestigious event of the Linley Group, it included dual-track presentations on the latest processor chips, processor IP and other technology required to efficiently process neural networks, packets, vision, and other workloads used in deep learning, embedded, communications, automotive, Internet-of-Things (IoT), and server designs.

Within the Linley Processor Conference 2017, Dr. Iakovos Stamoulis, Chief Technology Officer and co-founder of Think Silicon, made a presentation entitled “Ultralow-Power 3D Micro-GPU for IoT-Class Devices” presenting, inter alia, the performance and power analysis tools developed in the LPGPU2 project. The emerging Internet-of-Things market, with display devices limited in area, performance, memory, thermal dissipation and battery capacity is adding design challenges for engineers. The end-user is expecting the same fluid interaction and high–quality graphical-user-interface (GUI) experience known from their smartphones and tablets. These demands cannot be met through hardware improvements alone, but the software must fully exploit the available resources.

To answer these challenges, LPGPU2 proposes to aid the application developer in creating software for low-power GPUs by providing a complete performance and power analysis process for the programmer.

LPGPU2 @ Conference on Design and Architectures for Signal and Image Processing (DASIP 2017)

The LPGPU2 consortium participated in the Conference on Design and Architectures for Signal and Image Processing (DASIP 2017) held between 27 – 29 September 2017 at Dresden, Germany. DASIP provides an inspiring international forum for latest innovations and developments in the field of leading-edge embedded signal processing systems and was considered as important dissemination opportunity for the project towards reaching its targeted audiences.

Within DASIP 2017, Think Silicon made a presentation entitled “Enabling GPU Software Developers to Optimize Their Applications – The LPGPU2 Approach” presenting in brief the achievements made in the first phase of the project (till month 18) and focusing on the progress made in applications; in power measurement, estimation, and modelling; and in the analysis and visualization tool suite. The presentation was given by Katerina Pontzolkova (GPU Performance Engineer at Think Silicon) and the related session was chaired by Georgios Keramidas (Technical Coordinator of the LPGPU2 project and CSO of Think Silicon).

Visualizing CPU (ARM) assembly and performance counters!

LPGPU2 tool extended to visualize CPU (ARM) performance counters, as well as the arm assembly on a Xilinx ZC702 APSoC running Android 6.0 in which Nema GPUs are used as image composition engines:

Capturing and visualizing CPU (ARM) performance counters!

LPGPU2 tool extended to capture and visualize CPU (ARM) performance counters on a Xilinx ZC702 APSoC running Android 6.0 in which Nema GPUs are used as image composition engines:

Getting to know……Think Silicon

Think Silicon is an R&D intensive SME founded in 2007 specializing in high performance – low power Graphics IP semiconductor modules. As a fabless company, Think Silicon focus is on the design, development and marketing of products and formation of strategic alliances to achieve synergies, help reduce the entry costs, increase brand awareness and reach target customers. Working closely with customers and silicon wafer manufacturers around the world, the company has built a strong portfolio of silicon proven products that includes GPUs, display processors, and graphics accelerators for the IoT, Wearable and broader display devices markets, and its growing demand for ultra-low power, area and memory constrained SoCs. Company’s customers are leading fabless semiconductor companies like Lattice Semiconductors and that Sequans Communications.

The LPGPU2 team from Think Silicon (from right to left): Georgios Keramidas, Katerina Pontzolkova, Ignacio Aransay, Konstantinos Alexiou, and Chrysa Kokkala

Read more »

Think Silicon in 4YFN 2017 Barcelona

After a bustling CES in Las Vegas, we are heading to nother exciting event with the 4Y4N/MWC in Barcelona!

IoT has arrived in different forms. Smart connected devices, either worn on the wrist or as embedded and fixed installed solutions in your smart-home are here to stay! Whether for fitness, health, security, productivity or entertainment, many of those applications require a graphically rich display experience and ultra-low power consumption.

At MWC we will demonstrate the first Ultra-Low power FPGA-GPU, VR / Image processing applications, and our latest SDK API development tool platform.

By continuing to use the site, you agree to the use of cookies. more information

The cookie settings on this website are set to "allow cookies" to give you the best browsing experience possible. If you continue to use this website without changing your cookie settings or you click "Accept" below then you are consenting to this.

Close