A lightweight Python-based GPU architecture simulator that demonstrates how parallel threads, registers, memory, and instructions work on a GPU.
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Updated
Nov 8, 2026 - Python
A lightweight Python-based GPU architecture simulator that demonstrates how parallel threads, registers, memory, and instructions work on a GPU.
Synthesizable 16-lane SIMT GPU compute unit in SystemVerilog with a bit-exact Python golden model, assembler, constrained-random verification (200/200 seeds) and an RTL performance study: latency hiding, bank conflicts, branch divergence.
Tiny tensor compiler: one tensor program compiled to a GPU simulator (tiny-gpu) and a systolic-array TPU (tiny-tpu), checked bit-exact against numpy.
SIMT GPU warp execution simulator tracking active thread divergence masks, reconvergence points, and warp vote intrinsics (__ballot_sync, __all_sync, __any_sync).
CPU-runnable GPGPU lab: SIMT execution model, Triton-style IR/compiler, operator fusion, shared-memory tiling, PyTorch custom ops / compile backend / PrivateUse1 skeleton, and real Tesla-T4 measurements reconciled against the cost model.
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