- NVIDIA Toolsets Target GPU Acceleration of Deep Learning, Other Algorithms for High-Performance Computing
- Jeff Bier’s Impulse Response—Neural Network Processors: Has Their Time Come?
- Case Study: Algorithm Optimizations Efficiently Utilize Processor Features
- Analog Devices' SHARC Doubles Up, Adds ARM Option
- CogniVue's "Opus" APEX Generation 3: Vision Processing With Implementation Flexibility
InsideDSP — In-depth analysis and opinion
Your company’s core expertise lies in developing innovative digital signal processing algorithms, not in porting and optimizing those algorithms to any of the dozens of processors that your customers use. But optimized implementations are often critical to enable customers to utilize your
NVIDIA Toolsets Target GPU Acceleration of Deep Learning, Other Algorithms for High-Performance Computing
July 22, 2015 | Write the first comment.
"General-purpose GPU" (or "GPGPU") refers to the use of graphics processors for a variety of non-graphics tasks, and is a frequently discussed topic here at InsideDSP . GPUs are massively parallel processors, originally designed to only handle vertex and pixel operations.
Lately, neural network algorithms have been gaining prominence in computer vision and other fields where there's a need to extract insights based on ambiguous data. As I wrote last year , classical computer vision algorithms typically attempt to identify objects by first detecting small
BDTI is well known for its software-related capabilities: performance- and power consumption-related benchmarking , for example, along with algorithm evaluation and development and optimization work . In such projects, BDTI frequently employs semiconductor manufacturers' evaluation boards
Jeff Bier’s Impulse Response—What Does Semiconductor Industry Consolidation Mean for Embedded Systems Designers?
The semiconductor industry has been on a head-spinning merger binge lately. NXP is acquiring Freescale. Avago is acquiring Broadcom. Intel is acquiring Altera. Much has been written about the motivations for these mergers, and about the implications for investors in the merged firms. But so far,
The SHARC DSP family has long been a design staple of mid-range and high-end audio, industrial and other digital signal-processing intensive applications. With its two new series of products , Analog Devices delivers dual-core SHARC to the market for the first time. And the ADSP-SC58x devices also
June 29, 2015 | Write the first comment.
Practical computer vision (i.e. "embedded vision") is rapidly becoming a mainstream reality . Numerous processor chip and core suppliers have responded to increasing market demand with a variety of processor options. One of the first companies to target the vision processor space,
Semiconductor memory is increasing in capacity and becoming more cost-effective all the time. Yet, plenty of deeply embedded applications still exist for which every spare byte of RAM or flash memory is a precious commodity, especially those leveraging on-SoC storage versus discrete components.
These days we all have smart phones. Smart watches recently received a big boost with Apple's entry. And there is much talk of smart cities, smart factories, smart homes, smart trash receptacles...there's even a smart pacifier for your baby. I'm starting to feel like the term
The "Internet of Things" (IoT), one of the hottest topics in technology today, is widely anticipated to be a notable driver of both semiconductor and software demand in coming years. Key to an understanding of the IoT opportunity, as a recent article published on the Embedded Vision