Two-core GPU on a $30 FPGA: what to assess
Published on July 9, 2026, the article describes a two-core GPU implemented on a $30 FPGA, running AI model inference at 81 MHz.
Source: Uma GPU de dois núcleos implementada em um FPGA de US$ 30 (x.com). Text prepared with AI from this source.
What happened and what to do
Published on July 9, 2026, the article presents a two-core GPU implemented on a $30 FPGA, running AI model inference at 81 MHz. The project includes a 16-bit ISA, assembler, J++ language and compiler, as well as branch divergence and warp scheduling. The article highlights the ISA, compiler and scheduling as concrete examples of GPU architecture implemented in hardware.
For a company, this case can inform an assessment of inference on resource-constrained devices. A practical project could compare model and workload requirements with hardware limits, measure latency and power use, and define a monitoring and testing pipeline. Implementation could include API integration and operational controls, without assuming a low-cost FPGA can handle any production workload.
How the consultancy can help
Wendelmaques can diagnose workload requirements and constraints, scope an assessment of inference on limited hardware, and implement testing, monitoring and integrations suited to the company's environment.
Next step
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