Application-specific integrated circuits

Data Center Accelerator Market Size is Projected To Reach USD 69440 Million By 2027 at a CAGR Of 38.7% - Valuates Reports

Retrieved on: 
Monday, September 6, 2021
Computing, Technology, Data management, Cloud infrastructure, Application-specific integrated circuits, Cloud storage, Cloud computing, Big data, Accelerator, Data center, Graphics processing unit, Internet of things

The global Data Center Accelerator Market size is projected to reach USD 69440 Million by 2027, from USD 6960.5 Million in 2020, at a CAGR of 38.7% during 2021-2027.

Key Points: 
  • The global Data Center Accelerator Market size is projected to reach USD 69440 Million by 2027, from USD 6960.5 Million in 2020, at a CAGR of 38.7% during 2021-2027.
  • The rise in parallel computing in artificial intelligence (AI) data centers is fueling the expansion of the data center accelerator market.
  • Because of the growing demand for AI-based solutions, cloud data centers are dominating the data center accelerator market.
  • These initiatives are projected to increase parallel computing in data centers, boosting the data center accelerator market over the forecast period.

Data Center Accelerator Market Size is Projected To Reach USD 69440 Million By 2027 at a CAGR Of 38.7% - Valuates Reports

Retrieved on: 
Monday, September 6, 2021
Computing, Technology, Data management, Cloud infrastructure, Application-specific integrated circuits, Cloud storage, Cloud computing, Big data, Accelerator, Data center, Graphics processing unit, Internet of things

The global Data Center Accelerator Market size is projected to reach USD 69440 Million by 2027, from USD 6960.5 Million in 2020, at a CAGR of 38.7% during 2021-2027.

Key Points: 
  • The global Data Center Accelerator Market size is projected to reach USD 69440 Million by 2027, from USD 6960.5 Million in 2020, at a CAGR of 38.7% during 2021-2027.
  • The rise in parallel computing in artificial intelligence (AI) data centers is fueling the expansion of the data center accelerator market.
  • Because of the growing demand for AI-based solutions, cloud data centers are dominating the data center accelerator market.
  • These initiatives are projected to increase parallel computing in data centers, boosting the data center accelerator market over the forecast period.

Artificial Intelligence (AI) Chips Market to grow by USD 73.49 billion|Technavio

Retrieved on: 
Wednesday, August 4, 2021
Computing, Technology, Computer engineering, Hardware acceleration, Application-specific integrated circuits, Artificial intelligence, Integrated circuits, GPGPU, Field-programmable gate array, Graphics processing unit, Intel

NEW YORK, Aug. 3, 2021 /PRNewswire/ -- Technavio forecasts the artificial intelligence (AI) chips market to grow by USD73.49 billion, progressingat a CAGR of over51% during 2021-2025.

Key Points: 
  • NEW YORK, Aug. 3, 2021 /PRNewswire/ -- Technavio forecasts the artificial intelligence (AI) chips market to grow by USD73.49 billion, progressingat a CAGR of over51% during 2021-2025.
  • The artificial intelligence (AI) chips market report offers a comprehensive analysis of the strategies adopted by vendors and the trends, drivers, and challenges affecting the market size.
  • The Artificial Intelligence (AI) Chips Market is segmented by product (ASICs, GPUs, CPUs, and FPGAs) and geography (North America, Europe, APAC, South America, and MEA).
  • The artificial intelligence (AI) chips market covers the following areas:

CVEDIA Joins the NVIDIA Metropolis Program, Focusing on Synthetic Data to Accelerate Edge AI Applications

Retrieved on: 
Thursday, July 29, 2021
Computing, Computer engineering, Artificial intelligence, Technology, Graphics hardware, GPGPU, Application-specific integrated circuits, Virtual reality, Nvidia, Graphics processing unit, Applications of artificial intelligence, AI accelerator

CVEDIA is announcing a suite of custom tools including synthetic training data generation, deep learning analytics, algorithm optimization, and hardware fitting to accelerate development for edge AI applications.

Key Points: 
  • CVEDIA is announcing a suite of custom tools including synthetic training data generation, deep learning analytics, algorithm optimization, and hardware fitting to accelerate development for edge AI applications.
  • Synthetic data generated from simulations provide an inexpensive alternative to the real-world data used to train AI algorithms.
  • Metropolis partners have the opportunity to gain early access to NVIDIA platform updates to enhance and accelerate their AI application development efforts.
  • "We're looking forward to providing AI developers with data and algorithms built ready to deploy on NVIDIA GPU-accelerated systems and applications," said Arjan Wijnveen, CEO and co-founder of CVEDIA.

GBT Considers Using an AI Accelerator for its xCalibre (internal project name) Pattern Recognition Technology

Retrieved on: 
Wednesday, July 28, 2021
Academic disciplines, Articles, Computational neuroscience, Technology, Application-specific integrated circuits, Computer optimization, Artificial intelligence, Cybernetics, AI accelerator, Accelerator, Artificial general intelligence

GBT is now evaluating to accompany xCalibre with a complementary AI accelerator hardware.

Key Points: 
  • GBT is now evaluating to accompany xCalibre with a complementary AI accelerator hardware.
  • An AI accelerating system is a high-performance hardware that is designed to work in conjunction with an AI algorithm, enabling ultra-fast data processing.
  • A high level of processing optimization can be achieved by using a combination of AI programming with specifically designed hardware for it.
  • GBT evaluates adapting its AI algorithms with accelerating hardware targeting to significantly boost its xCalibre imaging performance.

OSS to Demonstrate Long-Range Visual Observation System at Sea-Air-Space Conference, August 2-4, 2021

Retrieved on: 
Tuesday, July 27, 2021
Computer engineering, Electronic engineering, Computing, Application-specific integrated circuits, Electromagnetic spectrum, GPGPU, Graphics hardware, Graphics processing unit, Infrared

The system supports multi-spectrum real-time observation at up to 30 nautical miles.

Key Points: 
  • The system supports multi-spectrum real-time observation at up to 30 nautical miles.
  • The all-weather ruggedized system includes military grade electro-optical and infrared video sensors, a proven enterprise AI framework, and high-performance edge AI inference system powered by OSS.
  • Hosted by the Navy League of the United States, Sea-Air-Space attracts maritime leaders from sea services around the globe.
  • OSS brings unique expertise in high speed PCIe interconnect and scalable GPU compute systems as required by the most demanding military and aerospace applications.

Maxim Integrated's Hand-Held Camera Cube Reference Design Enables Artificial Intelligence at the Edge for Vision and Hearing Applications

Retrieved on: 
Tuesday, July 20, 2021
Articles, Science and technology, Technology, Emerging technologies, Application-specific integrated circuits, Ambient intelligence, Digital technology, Internet of things, Technology assessment, Artificial intelligence, AI accelerator, Accelerator

The MAXREFDES178# enables ultra-low-power internet of things (IoT) devices to implement hearing and vision and showcases the MAX78000 low-power microcontroller with neural network accelerator for audio and video inferences.

Key Points: 
  • The MAXREFDES178# enables ultra-low-power internet of things (IoT) devices to implement hearing and vision and showcases the MAX78000 low-power microcontroller with neural network accelerator for audio and video inferences.
  • But the MAXREFDES178# camera cube demonstrates how AI can live on a low-power budget, enabling applications that are time- and safety-critical to operate on even the smallest of batteries.
  • The MAX78000's AI accelerator slashes the power of AI inferences up to 1,000x for vision and hearing applications, as compared to other embedded solutions.
  • Maxim Integrated, an engineer's engineering company, exists to solve the designer's toughest problems in order to empower design innovation.

Inspur Releases Liquid Cooled AI Server With NVIDIA A100 GPUs at ISC High Performance Digital 2021

Retrieved on: 
Monday, June 28, 2021
Networks, Internet, Hardware, Electronic design automation, Data management, Consumer electronics, Technology, Other Technology, Computing, Computer engineering, Technology, GPGPU, Fabless semiconductor companies, Application-specific integrated circuits, Graphics hardware, Coprocessors, Nvidia, Inspur, Graphics processing unit, Advanced Micro Devices

Today at ISC High Performance 2021 Digital , the event for high performance computing, machine learning, and data analytics, Inspur Information, a leading IT infrastructure solution provider, announces its new liquid cooling AI server, NF5488LA5.

Key Points: 
  • Today at ISC High Performance 2021 Digital , the event for high performance computing, machine learning, and data analytics, Inspur Information, a leading IT infrastructure solution provider, announces its new liquid cooling AI server, NF5488LA5.
  • NF5488LA5 is equipped with two AMD EYPC 7003 series processors and eight NVIDIA A100 Tensor GPUs in a 4U chassis fully connected by NVSwitch.
  • The system topology adopts an ultra-low latency design to maximize the communication performance between the processor and the AI accelerator.
  • It is also the only GPU server submitted that ran the NVIDIA A100 GPU at 500W TDP via liquid cooling technology.

SiMa.ai and The University of Tübingen Collaborate to Accelerate Low-Power Artificial Intelligence at the Embedded Edge While Reducing AI Compute Carbon Footprint

Retrieved on: 
Tuesday, June 15, 2021
University, Data management, Education, Technology, Semiconductor, Other Science, Other Technology, Research, Software, Networks, Science, GPGPU, Computing, Computer engineering, Parallel computing, Application-specific integrated circuits, Graphics hardware, Cloud infrastructure, Computer architecture, The University of Tübingen, SiMa.ai, THE UNIVERSITY OF TüBINGEN, SIMA.AI

SiMa.ai announced today its joint collaboration with the Department for Computer Science at the University of Tbingen in the Hardware-Agnostic Artificial Intelligence for Embedded project.

Key Points: 
  • SiMa.ai announced today its joint collaboration with the Department for Computer Science at the University of Tbingen in the Hardware-Agnostic Artificial Intelligence for Embedded project.
  • Through this important research project, the University of Tbingen is bringing together the academic community and top industry leaders to address and bridge the gap from high performance, high-energy embedded compute to high performance, low-power compute for embedded edge applications.
  • Software solutions that minimize hardware dependencies greatly reduce engineering development costs and aid in accelerating application migration, development, and deployment velocities.
  • SiMa.ai is a machine learning company transforming the embedded edge market through high-performance compute at the lowest power.

NVIDIA AI Enterprise Software Drives New Wave of Certified Systems from World’s Leading Manufacturers

Retrieved on: 
Tuesday, June 1, 2021
Computing, Computer engineering, Electronic engineering, Nvidia, GPGPU, Application-specific integrated circuits, Graphics hardware, NVLink, Graphics processing unit, DataDirect Networks, Christofari

SANTA CLARA, Calif., May 31, 2021 (GLOBE NEWSWIRE) -- COMPUTEX -- NVIDIA today announced dozens of new servers certified to run NVIDIA AI Enterprise software, marking a rapid expansion of the NVIDIA-Certified Systems program, which has grown to include more than 50 systems from the worlds leading manufacturers.

Key Points: 
  • SANTA CLARA, Calif., May 31, 2021 (GLOBE NEWSWIRE) -- COMPUTEX -- NVIDIA today announced dozens of new servers certified to run NVIDIA AI Enterprise software, marking a rapid expansion of the NVIDIA-Certified Systems program, which has grown to include more than 50 systems from the worlds leading manufacturers.
  • These include running the NVIDIA AI Enterprise suite of AI and data analytics software on VMware vSphere to deploy an AI-ready enterprise platform that scales AI workloads, NVIDIA Omniverse Enterprise for design collaboration and advanced simulation and Red Hat OpenShift for AI development.
  • Enterprises across every industry need to support their innovative work in AI on traditional data center infrastructure, said Manuvir Das, head of Enterprise Computing at NVIDIA.
  • These provide leading AI performance with four or eight NVIDIA A100 GPUs, NVIDIA NVLink GPU interconnects, NVIDIA InfiniBand networking, and NVIDIAs AI and HPC software stack.