Fullmoonfever
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Ahh....hindsight is such a wonderful thing to give clues as to how long some things could have been brewing.
From a couple of months ago.
www.nextplatform.com
Software, Not Hardware, Will Drive Quantum and Neuromorphic Computing
Jeffrey Burt
2 months ago
As with the Quantum SDK, Intel initially had no intention of creating a software framework out of the software developed and used in-house for neuromorphic computing, according to Mike Davies, senior principal engineer and director of the chip maker’s Neuromorphic Computing Lab. However, it became clear that the lack of a general-purpose software stack was hobbling the industry’s efforts in the field.
“Until Lava, it’s been very difficult for groups to build on other groups’ results even within our own community because software tends to be very siloed, very laborious to construct these compelling examples,” Davies told journalists. “But as long as those examples are developed in a way that cannot be readily transferred between groups and you can’t design those at a high level of abstraction, it becomes very difficult to move this into the commercial realm where we need to reach a broad community of mainstream developers that haven’t spent years doing PhDs in computational neuroscience and neuromorphic engineering.”
Lava is an open-source framework with permissive licensing, so the expectation is that other neuromorphic chip manufacturers – which include the likes of IBM, Qualcomm, and BrainChip – will port Lava to their own frameworks. It’s not proprietary, though Intel is the major contributor to it, Davies said.
The latest iteration of Lava is version 0.5, though the company has been steadily rolling out releases of Lava to GitHub, he said. It also illustrates, along with circuit improvements in Loihi 2, the advancements made in the chip for running deep feed forward neural networks, a basic type of network used in some supervised learning uses. There are fewer chip resources needed to support these networks, the inference operation is up to 12X faster than Loihi 1, and 50X more energy efficient.
These aren’t the types of workloads that Loihi was designed to support – GPUs and other accelerators can run deep feed forward networks well. And Intel is aware of this. “It is very important that we support feedforward neural networks of the kind that everyone is using and loves today because they’re just an important building block for future neuromorphic applications.” Davies said.
From a couple of months ago.
Software, Not Hardware, Will Drive Quantum and Neuromorphic Computing
In emerging computing fields like quantum computing and neuromorphic computing, hardware usually grabs the lion’s share of attention. You can see the
www.nextplatform.com
Software, Not Hardware, Will Drive Quantum and Neuromorphic Computing
Jeffrey Burt
2 months ago
As with the Quantum SDK, Intel initially had no intention of creating a software framework out of the software developed and used in-house for neuromorphic computing, according to Mike Davies, senior principal engineer and director of the chip maker’s Neuromorphic Computing Lab. However, it became clear that the lack of a general-purpose software stack was hobbling the industry’s efforts in the field.
“Until Lava, it’s been very difficult for groups to build on other groups’ results even within our own community because software tends to be very siloed, very laborious to construct these compelling examples,” Davies told journalists. “But as long as those examples are developed in a way that cannot be readily transferred between groups and you can’t design those at a high level of abstraction, it becomes very difficult to move this into the commercial realm where we need to reach a broad community of mainstream developers that haven’t spent years doing PhDs in computational neuroscience and neuromorphic engineering.”
Lava is an open-source framework with permissive licensing, so the expectation is that other neuromorphic chip manufacturers – which include the likes of IBM, Qualcomm, and BrainChip – will port Lava to their own frameworks. It’s not proprietary, though Intel is the major contributor to it, Davies said.
The latest iteration of Lava is version 0.5, though the company has been steadily rolling out releases of Lava to GitHub, he said. It also illustrates, along with circuit improvements in Loihi 2, the advancements made in the chip for running deep feed forward neural networks, a basic type of network used in some supervised learning uses. There are fewer chip resources needed to support these networks, the inference operation is up to 12X faster than Loihi 1, and 50X more energy efficient.
These aren’t the types of workloads that Loihi was designed to support – GPUs and other accelerators can run deep feed forward networks well. And Intel is aware of this. “It is very important that we support feedforward neural networks of the kind that everyone is using and loves today because they’re just an important building block for future neuromorphic applications.” Davies said.
next perth catch up let’s definitely discuss!
