{"id":11890,"date":"2022-12-27T07:00:00","date_gmt":"2022-12-27T15:00:00","guid":{"rendered":"https:\/\/formtek.com\/blog\/?p=11890"},"modified":"2022-06-04T16:31:50","modified_gmt":"2022-06-05T00:31:50","slug":"hardware-software-codesign-application-specific-optimized-architecture","status":"publish","type":"post","link":"https:\/\/formtek.com\/blog\/hardware-software-codesign-application-specific-optimized-architecture\/","title":{"rendered":"Hardware\/Software CoDesign: Application-Specific Optimized Architecture"},"content":{"rendered":"\n

Hardware\/Software co-design is an approach to computing that tries to take into account both hardware and software design to create a system which can optimally perform computations for a specific task. Most computers today are general purpose and can be programmed to address any type of computation, but their performance is necessarily subpar for specific applications when compared to systems that are developed, optimized, and tuned for those applications.<\/p>\n\n\n\n

Andy Heinig<\/a>, group leader at Fraunhofer IIS, said that<\/a> “CoDesign is a very good approach to realize highly optimized hardware for a given problem. But this high level of optimization is one of the drawbacks of the approach. Optimized designs are very expensive, and as a result such an approach can only work if the number of produced devices is very high. Most applications do not need optimized hardware, instead using more flexible architectures that can be re-used in different applications.\u201d<\/p>\n\n\n\n

One area in particular where co-designed systems may be worth the effort is for AI.<\/p>\n\n\n\n

Tim Kogel<\/a>, principal applications engineer at Synopsys, said that<\/a> “AI is clearly driving a new golden age of computer architecture. Moore\u2019s Law is running out of steam, and with a projected 1,000X growth of design complexity in the next 10 years, AI is asking for more than Moore can deliver. The only way forward is to innovate the computer architecture by tailoring hardware resources for compute, storage, and communication to the specific needs of the target AI application.\u201d<\/p>\n\n\n\n

Suhas Mitra<\/a>, product marketing director at Cadence, said that<\/a> \u201ceverything has a challenge and also a peril. You build something for a type of workload, and it doesn\u2019t pan out because it took three years and now the market is moving in a different direction. Models are evolving, and not just by scaling. Today, for natural language processing, transformer architectures are taking over. If you build an ASIC, you harden everything. You are playing the game of power and area, and what will succeed in a market. There are certain markets where people favor FPGAs because they do not have to harden everything. They can keep some functionality in the fabric. Those are more flexible. Like anything else, there\u2019s a pro and a con to every decision that you make.\u201d<\/p>\n

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Hardware\/Software co-design is an approach to computing that tries to take into account both hardware and software design to create a system which can optimally perform computations for a specific task. Most computers today are general purpose and can be…<\/span><\/p>\n

Read more ›<\/a><\/div>\n

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