Posted by Hyderabad: Blaize, erstwhile Thinci, an AI focused company has unveiled a new computing architecture Blaize Graph Streaming Processor (GSP).
Blaize GSP is a next-generation computing architecture that precisely meets the demands and complexity of new computational workloads found in artificial intelligence (AI) applications.
The Blaize GSP architecture and Blaize Picasso software development platform deliver breakthroughs in computational efficiency. The solution blends dynamic data flow methods and graph computing models with fully programmable proprietary SOCs. This allows the platform to exploit the native graph structure inherent in neural network workloads all the way through run-time.
The massive efficiency multiplier is delivered via a data streaming mechanism, where non-computational data movement is minimized or eliminated. This gives Blaize systems the lowest possible latency, reduces memory requirements and reduces energy demand at the chip, board and system levels.
Blaize GSP is the first fully programmable processor architecture and software platforms built from the ground up to be 100% graph-native. While there are many types of neural networks, all neural networks are graphs. With the inherent graph-native structure, developers can now build multiple neural networks and entire workflows on a single architecture that is applicable to many markets and use cases.
As part of Blaize’s growth strategy, the company has expanded its existing capacity in Hyderabad to accommodate 450 employees and emphasizing hiring skilled engineers from India.
Blaize products enable a range of existing and new AI use cases in the automotive, smart vision, and enterprise computing segments, where the company is engaged with early access customers. These AI systems markets are projected to grow rapidly as the disrupting influence of AI transforms entire industries and AI functionality becomes a “must-have” requirement for new products.
Blaize was founded on a vision of a better way to compute the workloads of the future by rethinking the fundamental software and processor architecture. It is a special day for the entire team in Hyderabad which has played a crucial role in helping us in realising this vision,” said Dinakar Munagala, Co-founder and CEO, Blaize.
“We see demand from customers across markets for new computing solutions that address the immediate unmet needs for technology built for the emerging age of AI, and solutions that overcome the limitations of power, complexity and cost of legacy computing,” added Munagala.
“Blaize is very innovative, our important business partner,” said Yukihide Niimi, CEO of NSITEXE and DENSO Advisory Board member.
“DENSO is demonstrating leadership in many areas as the automotive industry undergoes extraordinary technology changes. NSITEXE was established to catch up such technology change and to accelerate development of flexible compute IP solutions like DFP. NSITEXE is willing to work together with Blaize to boost the flexible Graph (Data Flow) compute technology ecosystem,” added Niimi.
“I have been watching Blaize for several years and saw early on that their graph-native architecture would be particularly well suited to a wide range of AI and robotics workloads,” said Schuyler Cullen, VP AI & Robotics, Samsung Strategy and Innovation Center.
“The proliferation of AI across multiple industries and application areas is dependent upon robust, programmable, efficient, scalable, high-performance hardware, that extends AI processing from cloud data centers through to the end device, server or appliance,” said Aditya Kaul, Research Director, Tractica.
“It’s becoming clear that traditional processing architectures will not be enough to meet the demands of this new emerging market, with new techniques like graph-based computing showing promise. Success will be defined by combining new computing approaches with modular hardware and a deployment-oriented software stack, all of which is part of the Blaize value proposition from day one,” added Kaul.
“Blaize’s vision of a native graph streaming processor (GSP) is relatively unique. The GSP is more general purpose than, say, a single-function ASIC for AI, and can consequently create opportunities in many markets, from Automotive to the Edge to the Cloud,” noted Karl Freund, Senior AI Analyst – Moor Insights & Strategy.
“The coming out of Blaize and its leading Graph Streaming Processor is extremely exciting,” says David (Dadi) Perlmutter, an angel investor, entrepreneur and former EVP and Chief Product Officer – Intel.
“As an initial investor in Blaize, I recognized early on the great efficiency of one of the first to market a complete solution designed from scratch, fully optimized for AI and Neural Network applications. The unprecedented efficiency is great for a wide range of edge applications, particularly the automotive market. I am proud of the team in delivering on the promise,” added Perlmutter.