Flex Logix Technologies, Inc. announced that it has partnered with Intrinsic ID to ensure that any device using its eFPGA remains secure and can’t be modified maliciously, whether through physical attacks or remote hacking. The integration of Intrinsic ID SRAM Physical Unclonable Function (PUF) military-grade security IP with Flex Logix’s EFLX eFPGA provides a device […]
Neural Networking
What’s a Neural microcontroller?
The ability to run neural networks (NNs) on MCUs is growing in importance to support artificial intelligence (AI) and machine learning (ML) in the Internet of Things (IoT) nodes and other embedded edge applications. Unfortunately, running NNs on MCUs is challenging due to the relatively small memory capacities of most MCUs. This FAQ details the […]
ASIC combines image processors, neural processing for automotive apps
OMNIVISION, together with Seeing Machines announce the automotive industry’s first dedicated driver monitoring system (DMS) and occupant monitoring system (OMS) application-specific integrated circuit (ASIC) that combines an image signal processor (ISP) and is powered by Seeing Machines’ Occula Neural Processing Unit (NPU). OMNIVISION announced the world’s first dedicated DMS ASIC with an integrated AI NPU, […]
Maxim captures LEAP Award in Embedded Computing
Executing AI inferences at less than 1/100th the energy of other embedded solutions to dramatically improve run-time for battery-powered AI applications, helped earn Maxim Integrated’s MAX78000 low-power, neural network, accelerated MCU a LEAP Award in Embedded Computing. More than 100 entries were received for the annual competition which celebrates the most innovative and forward-thinking products […]
Sub-100 fsec point-of-use clock IC helps meet next-generation PAM4 requirements
Renesas Electronics Corporation expanded its timing solutions portfolio with a new sub-100fs point-of-use clock solution for data center, server, and network infrastructure markets. The new FemtoClock2 family includes ultra-low jitter clock generators and jitter attenuators in a small 4×4 mm2 package, enabling cost-effective and simple clock tree implementation for next-generation, high-speed interconnect designs. Featuring best-in-class […]
FPGAs augment NICs for cloud data center uses
Inventec (2356.TW), in collaboration with Intel, announces the release of the new Inventec FPGA SmartNIC C5020X that complements the Intel FPGA SmartNIC C5000X platform architecture. Inventec is one of Intel’s first ecosystem partners to leverage this platform. The FPGA SmartNIC C5020X works to extend traditional Network Interface Controllers (NICs) beyond its existing restrictions for the […]
4U GPU system delivers 6x AI training performance, 7x inference workload capacity
Super Micro Computer, Inc., announced the doubling of GPU capabilities with a new 4U server supporting eight NVIDIA HGX A100 GPUs. Supermicro offers the industry’s broadest portfolio of GPU systems spanning 1U, 2U, 4U, and 10U GPU servers and SuperBlade servers over a wide range of customizable configurations. Supermicro now offers the industry’s widest and […]
How “green” is your Artificial Intelligence?
Artificial intelligence (AI) systems face a set of conflicting goals: being accurate (consuming large amounts of computational power and electrical power) and being accessible (being lower in cost, less computationally intensive, and less power-hungry). Unfortunately, many of today’s AI implementations are environmentally unsustainable. Improvements in AI energy efficiency will be driven by several factors, including […]
Benchmarking AI from the edge to the cloud
Artificial Intelligence (AI), machine learning (ML), and deep learning (DL) are fast-changing and complex fields. Until relatively recently, there were no performance benchmarks for AI, ML, or DL systems. That is changing. Today, several industry organizations have developed AI, and ML benchmarks, with more complex benchmarks for DL coming soon. Those efforts stretch from the […]
Software-based inference accelerator speeds AI deployment on edge devices
A software-based inference accelerator is said to drastically improve deep learning performance on any existing hardware. Today, deep learning deployments are very limited and are primarily optimized for the cloud; and, even in these cases, they incur extensive processing costs, significant memory requirements, and expensive power costs, due to intensive computing demands. These challenges also […]