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.

LPGPU2 paper accepted at DATE 2018 conference

The paper “Optimal DC/AC Data Bus Inversion Coding” by Jan Lucas, Sohan Lal and Ben Juurlink has been accepted as regular paper at the DATE 2018 conference. In the paper a new method for data encoding is presented that reduces the energy consumption of the data transfer between CPU or GPU by up to 6%.  DATE (Design, Automation and Test in Europe) will held in March at the International Congress Center Dresden. The selection process was very competitive with an acceptance rate of regular papers of only 23.7%.

Optimal DBI Encoding as a shortest path problem

Spin Digital at InterBEE 2017 in Tokyo

Spin Digital Video will participate at InterBEE 2017 from November 15-17 at the Makuhari Messe in Tokyo, at the booth 8105.

Spin Digital at InterBEE Tokyo

Spin Digital is going to present demonstrations of the new versions of its HEVC solutions including: 8K media player and SDK. Read more »

Codeplay add OpenCL kernel code coverage!


AMD’s opinion of LPGPU2

Codeplay recently reached out to AMD, and asked for their thoughts on what we are doing with LPGPU2 and how we are leveraging their open source CodeXL tool.

AMD stated “The LPGPU2 project validates AMD’s decision 2 years ago to create GPUOpen and open up the source code to our tools and libraries.  Seeing CodeXL evolve through 3rd party participation to be used in new markets is very satisfying and a clear endorsement of our strategy.”

We at LPGPU2 are very pleased to base our work on the technologies made freely available by AMD’s forward looking decision to open source CodeXL.


Ben Juurlink and Georgios Keramidas guest editors of special issue of International Journal of Reconfigurable Computing

Ben Juurlink, coordinator of LPGPU2, and Georgios Keramides, technical coordinator of LPGPU2, are lead guest editor and resp. guest editor of the special issue on “Approximating (Deep) Neural Networks and Approximate Computing Using Reconfigurable Hardware” of the International Journal of Reconfigurable Computing. The International Journal of Reconfigurable Computing is published by Hindawi, which is one of the world’s largest publishers of peer-reviewed, fully Open Access journals. The EU strongly supports Open Access publications. Other guest editors of this special issue are Stephan Wong of TU Delft in the Netherlands; Antonio Beck of Federal University of Rio Grande do Sul in Porto Alegre in Brazil; and Chao Wang of the University of Science and Technology China in Suzhou, China. The Call for Papers can be found here

Codeplay & Samsung update on remote profiling

This blog in brief is about Codeplay modifying CodeXL, AMD’s open sourced profiling tool, to be able for the first time to capture and display power usage data from a standard Android device. Codeplay have created a video to demonstrate this new capability. By adding this new capability LPGPU2 has opened up far reaching possibilities of profiling non AMD hardware and/or remote low power devices utilizing mobile OS’s such as Android and Tizen.

About the CodeXL <-> Android power profiling

LPGPU2’s version of CodeXL has added a new capability to be able to communicate with and retrieve power data from standard Android devices or any other device that implements the DC API (see below for more on this new API) and makes the data captured accessible to CodeXL via a custom extension to its remote protocol.

By extending CodeXL’s remote protocol to communicate with the Android device it is now able to receive power data sent from any remote application or library which implements the API on that device. We intend to further augment this by adding API call data as well as other items of interest.

The CodeXL remote device protocol remains backward compatible. CodeXL can update its live visualisations in real time while also recording the new power data to its standard but extended database for static analysis offline later (see below for more information). Again, like the remote protocol the database layer within CodeXL remains compatible with existing CodeXL projects.

The Android device is a standard phone, which has not been rooted. This ability to allow profiling to take place on any standard device is important for ease of use and to increase the number of possible users.

The phone has a custom application installed on it which installs a service which listens out for CodeXL to attach to it. When a connection is established the service provides CodeXL with information about the applications it can profile. The user can then start the selected application which commences sending profiling data back to CodeXL using the DC API.

For this demonstration the version of CodeXL shown is only able to communicate with an Android OS type device but this will change to manage communication with applications on other OS / devices in the future. For the LPGPU2 project Android is the primary mobile operating system.

The Data Collection (DC) API

At part of LPGPU2’s statement of work and early project planning it became clear that a standardised performance and power counter API was necessary to be developed and ready before trying to profile supported devices.

Rather than implement a different mechanism for each supported Khronos API the DC API was designed to support those APIs in a non-intrusive manner by being an API neutral solution to the problem of enumerating, describing, enabling, disabling and collecting data from disparate hardware with equally varied counter implementations.

The DC API has been developed by Samsung and implemented by Samsung and ThinkSilicon. The DC API can be implemented by an application or library on any remote device, not just an Android device.

Static Analysis

The beauty of being able to capture profiling data from a device is not just in the real time capture capability shown in the video but also when CodeXL is in offline mode permitting static analysis.

Samsung are developing as part of the LPGPU2 project a feedback engine which will analyze the captured data and feed back to the user efficiency anomalies. Codeplay have extended CodeXL’s data visualisations to highlight regions of interest within the profiling data from which the user can choose to examine the source code which is associated with the areas identified as possible sources of inefficiencies and be presented with advice and suggestions to improve their applications.

For more information on the Feedback engine please see the article “Farewell Borja and whither Feedback” on LPGU2’s web site.

Codeplay & Samsung deliver live power profiling from an Android device!

Working together closely Codeplay and Samsung have delivered remote power profiling from an Android device into the live power profiling view of CodeXL. This is a huge step forward and moves the tool suite a big step closer to full operation.


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).

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