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Qernel
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—— v1.0.0
Unlocking 100x Energy Efficient AI Inference:
Charge-domain Processing-in-Memory
Qernel AI proposes a radical rethinking of AI inference architecture by merging computation and memory through: Charge-domain processing, 3D stacking, Compute-in-Memory (CIM). This innovation tackles the "Memory Wall"—a critical bottleneck in traditional GPU-based systems where data transfer latency and bandwidth limitations throttle performance.
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Qcore : The 10× AI Accelerator That Says
“Who Needs Data Movement?”
The rapid acceleration of artificial intelligence has pushed the limits of today’s computing hardware, driving a massive need for faster, more efficient processing. Among the emerging solutions, Compute-In-Memory (CIM) stands out—bringing matrix-vector multiplication directly into memory arrays to drastically reduce data movement and power consumption.
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About
Blog
Careers
Contact
Qernel
AI
—— v1.0.0
About
Blog
Careers
Contact
About
Blog
Careers
Contact
V
.
1
.
0
.
0
Unlocking 100x Energy Efficient AI Inference:
Charge-domain Processing-in-Memory
Read More
Read More
Qernel AI proposes a radical rethinking of AI inference architecture by merging computation and memory through: Charge-domain processing, 3D stacking, Compute-in-Memory (CIM). This innovation tackles the "Memory Wall"—a critical bottleneck in traditional GPU-based systems where data transfer latency and bandwidth limitations throttle performance.
Coming soon