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TinyTorch/paper
Vijay Janapa Reddi 3c020f13d1 Revise Table 2 with balanced ML and Systems concepts
ML side additions (all actually taught):
- GELU, Tanh activations
- Xavier initialization
- log-sum-exp trick
- AdamW optimizer
- Cosine scheduling, gradient clipping
- Sinusoidal/learned positional encodings
- Causal masking
- LayerNorm, MLP
- Magnitude pruning, knowledge distillation

Systems side improvements (more concrete):
- Contiguous layout, dtype sizes
- Gradient memory multipliers (2x momentum, 3x Adam)
- im2col expansion
- Sparse gradient updates
- Attention score materialization
- KV cache sizing, per-layer memory
- Cache locality, SIMD utilization
- Confidence intervals, warm-up protocols
- Pareto optimization

Renamed "AI Olympics" to "Olympics" in table.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-19 20:56:32 -05:00
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TinyTorch Research Paper

Complete LaTeX source for the TinyTorch research paper.


Files


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  2. Create free account
  3. Upload paper.tex and references.bib
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Option 2: Local Compilation

./compile_paper.sh

Requires LaTeX installation (MacTeX or BasicTeX).


Paper Details

  • Format: Two-column LaTeX (conference-standard)
  • Length: ~12-15 pages
  • Sections: 7 complete sections
  • Tables: 3 (framework comparison, learning objectives, performance benchmarks)
  • Code listings: 5 (syntax-highlighted Python examples)
  • References: 22 citations

Key Contributions

  1. Progressive disclosure via monkey-patching - Novel pedagogical pattern
  2. Systems-first curriculum design - Memory/FLOPs from Module 01
  3. Historical milestone validation - 70 years of ML as learning modules
  4. Constructionist framework building - Students build complete ML system

Framed as design contribution with empirical validation planned for Fall 2025.


Submission Venues

  • ArXiv - Immediate (establish priority)
  • SIGCSE 2026 - August deadline (may need 6-page condensed version)
  • ICER 2026 - After classroom data (full empirical study)

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