Software Development

HSA Foundation Aims for Broader Adoption of Coherent Memory Standard for Heterogeneous Processors

Modern SoCs increasingly contain a variety of processing resources: one or more CPU cores and a GPU, often with a DSP, programmable logic, or one or multiple special-purpose co-processors for tasks such as computer vision. Properly harnessed, such heterogeneous processors often deliver impressive performance at low cost and low power consumption. But mapping applications onto heterogeneous processors is challenging. OpenCL, a specification standard language and runtime from the Khronos Group, Read more...

Movidius' Fathom Enables Embedded Deep Learning

In late January of this year, Movidius and Google broadened their collaboration plans, which had begun with 2014's Project Tango prototype depth-sensing smartphone. As initially announced, the companies’ broader intention to "accelerate the adoption of deep learning within mobile devices" was somewhat vague. However, as of earlier this month, at least some of the details of the planned collaboration become clearer, thanks to the unveiling of Movidius' Fathom Software Framework and Neural Read more...

Deep Learning and Digital Signal Processing: A Conversation with Cadence's Chris Rowen

Convolutional neural networks (CNNs) and other "deep learning" techniques are finding increasing use in a variety of detection and recognition tasks:  identifying music clips and speech phrases, for example, and finding human faces and other objects in images and videos. As a result, we’ve been covering deep learning concepts and implementations regularly in InsideDSP columns and news articles. Chris Rowen, Chief Technology Officer of Cadence Design Systems' IP Group, will be speaking about the Read more...

Case Study: From Platform Selection to Optimized Application: Vision System Design Success

As computer vision is deployed into a variety of new applications, driven by the emergence of powerful, low-cost, and energy-efficient processors, companies need to find ways to squeeze demanding vision processing algorithms into size-, weight-, power, and cost-constrained systems. Fortunately for its clients, BDTI's skill in benchmarking has armed it with unique skill in optimizing software to best exploit processor capabilities. It's also provided BDTI with an in-depth understanding of the Read more...

Case Study: Cool Algorithm, But Will It Fit in My Product?

Algorithms are the essence of digital signal processing; they are the mathematical "recipes" that transform signals in useful ways. Companies developing new algorithms, or considering purchasing or licensing algorithms, often need to assess whether an algorithm will fit within their processing budget—and thereby within their cost and power consumption targets. But estimating an algorithm's processing load can be difficult if the algorithm has not already been carefully mapped onto the target Read more...

Texas Instruments Sitara SoCs Integrate Diverse Processing Resources

It's becoming increasingly possible, thanks to APIs and languages such as Khronos' OpenCL, for applications to efficiently harness the heterogenous computing resources available in modern SoCs. And it's therefore increasingly common for SoC designers to include a variety of both general-purpose and function-specific parallel-processing cores on-chip, leveraging the prodigious transistor budgets available on modern lithography processes. These trends are fully evident with Texas Instruments' 28 Read more...

CEVA Software Framework Brings Deep Learning to Embedded Vision Systems

As Jeff Bier has mentioned in several of his recent columns, deep learning algorithms have gained prominence in computer vision and other fields where there's a need to extract insights from ambiguous data. Convolutional neural networks (CNNs) – massively parallel algorithms made up of layers of computation nodes – have shown particularly impressive results on challenging problems that thwart traditional feature-based techniques; when attempting to identify non-uniform objects, for example, or Read more...

Case Study: Digital Signal Processing Library Development Enables Effective Processor Deployments

As applications become more complex, and processors become more powerful, system developers increasingly rely on off-the-shelf software components to enable rapid and efficient application development. This is particularly true in digital signal processing, where application developers expect to have access to libraries of optimized building-block functions to speed their work. A leading SoC developer recently contracted BDTI to assist it in developing a comprehensive library of software Read more...

Case Study: Squeezing Big Algorithms into Small Power Budgets Enables Mobile Audio Quality

Today's smartphones are technological marvels that deliver an extraordinary range of capabilities from GPS-based navigation to sophisticated photography. But sometimes we just want to make a phone call. And particularly when we're on the move, who hasn't struggled to hear the other party or to be heard on a mobile call? Realizing the importance of intelligible phone calls – not to mention a strong need to differentiate their products – smartphone manufacturers are incorporating increasingly Read more...

Freescale Introduces New Embedded Processors and Modules

Back in early 2013, the smartphone market was red hot, as was demand for Amazon's Kindle and other e-book readers. And the tablet market, although comparatively nascent, was in a rapid growth phase, as was interest in alternative computer platforms such as Google's Chrome O/S-based products. The substantial processing demands of these and other similar applications are evident in the formidable resources integrated within Freescale Semiconductor's i.MX 6 family introduced that same year: one to Read more...