Commit Graph

76 Commits

Author SHA1 Message Date
Vijay Janapa Reddi
6191a039f6 Replace \paragraph{} with \noindent\textbf{} throughout paper
Converted all paragraph headings to bold text format for consistent
styling throughout the document. This improves visual consistency and
follows the requested formatting guidelines.

Changes:
- Paper Organization (introduction)
- Build/Use/Reflect cycle descriptions
- Why Milestones Matter
- The Six Historical Milestones
- Experiencing Performance Reality
- All future work subsection headings (Roofline Models, ASTRA-sim,
  Energy and Power Profiling, The Three-Tier Systems Pedagogy)

Table 3 remains correctly positioned in Systems Integration section
where performance trade-offs are discussed.

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

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-18 17:16:37 -05:00
Vijay Janapa Reddi
7089d0a8fc Remove remaining temporary files from paper directory
Cleaned up:
- FIGURE_SUMMARY.txt (temporary figure notes)
- INTRODUCTION_REVISED.tex (draft version, now integrated)

Build artifacts (.aux, .bbl, .blg) left unstaged as working files.

Research team reference documents retained for review:
- CITATIONS_TO_ADD.md
- CLAIM_EVIDENCE_MATRIX.md
- EVIDENCE_INVENTORY.md
- LITERATURE_REVIEW_ASSESSMENT.md
- NEW_CITATIONS.bib

🤖 Generated with Claude Code

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-18 17:06:31 -05:00
Vijay Janapa Reddi
4cf47a7443 Apply critical and high-priority research team fixes
CRITICAL FIXES (blocking issues):
1. Fixed corrupted bruner1960process citation (was citing 2023 infant mortality paper)
   - Now correctly cites Bruner's "The Process of Education" (1960)
2. Fixed corrupted perkins1992transfer citation (was citing wrong paper)
   - Now correctly cites Perkins & Salomon "Transfer of Learning" (1992)
3. Added systems thinking citation (Meadows 2008) for tacit knowledge framing
4. Added compiler pedagogy citation (Aho et al. 2006 Dragon Book)

HIGH-PRIORITY IMPROVEMENTS:
5. Consolidated validation caveats into ONE comprehensive scope paragraph
   - Removed defensive tone from individual contributions
   - Stronger framing: "demonstrated design patterns" vs "unvalidated claims"
   - Clear separation: technical correctness (proven) vs learning outcomes (hypothesized)

6. Broke dense introduction paragraph into two for readability
   - Para 1: Workforce statistics and demand
   - Para 2: Tacit knowledge problem and automation resistance

7. Sharpened MiniTorch comparison with concrete differentiation
   - Added: math-first vs systems-first pedagogical inversion
   - Added: progressive disclosure (unified API) vs separate abstractions
   - Made competitive positioning clearer and more specific

8. Added transitional bridge in Paper Organization paragraph
   - Improved flow from introduction to body sections

9. Renamed Contribution 3: "Replicable Educational Artifact" → "Open Educational Infrastructure"
   - More accurate, less generic
   - Added concrete details (historical milestone range, specific section references)

10. Added proper citations throughout contributions for grounding
    - Situated cognition, constructionism, cognitive load theory, cognitive apprenticeship
    - NBGrader infrastructure cited

Paper now compiles successfully (22 pages, 373KB).
Addresses all blocking issues identified by research team review.

🤖 Generated with Claude Code

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-18 17:06:00 -05:00
Vijay Janapa Reddi
91b6173374 Clean up temporary markdown files from paper directory
Removed temporary analysis and revision files:
- ACADEMIC_WRITER_BRIEF.md
- FIGURE_PROPOSALS.md
- FINAL_QUALITY_ASSESSMENT.md
- README_FIGURES.md
- REVISION_QUICK_REFERENCE.md

These files were created during iterative review process and are no longer needed.

Kept essential files:
- README.md (paper directory documentation)
- CRITICAL_FIXES_REMAINING.md (tracking document - can be removed once all fixes verified)

🤖 Generated with Claude Code

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-18 13:01:35 -05:00
Vijay Janapa Reddi
748967a705 Improve title and module flow diagram clarity
Title changes:
- Old: "A Framework for Learning ML Systems from Scratch, from Tensors to Systems"
- New: "Build Your Own Machine Learning Framework From Tensors to Systems"
- More active, clearer action-oriented framing

Module flow diagram improvements:
- Increased spacing: node distance 0.8cm→1.0cm (vertical), 1.2cm→1.8cm (horizontal)
- Added minimum width 1.8cm to all nodes for consistency
- Simplified arrows to show primary linear flow within each tier
- Reduced visual complexity while maintaining dependency clarity
- Better readability in two-column format

🤖 Generated with Claude Code

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-18 12:42:24 -05:00
Vijay Janapa Reddi
f87be35406 Reorder contributions: systems-first → progressive disclosure → artifact
Strategic reordering with flow improvements:

Old order (mechanism → philosophy → artifact):
1. Progressive Disclosure Pattern
2. Systems-First Curriculum Architecture
3. Replicable Educational Artifact

New order (WHAT → HOW → DELIVERABLE):
1. Systems-First Curriculum Architecture - leads with core novelty
2. Progressive Disclosure Pattern - explains enabler ("To make systems-first learning tractable...")
3. Replicable Educational Artifact - validates both innovations ("Both innovations are validated through...")

Flow improvements:
- Contribution 1: Added "directly addresses the workforce gap" to link back to introduction
- Contribution 2: Opens with "To make systems-first learning tractable" (flows from #1)
- Contribution 2: Added "solves the cognitive load challenge inherent in teaching both"
- Contribution 3: Changed to "Both innovations are validated through" (flows from #1+#2)
- Paper Organization: Reordered section references to match (sec:curriculum,sec:systems,sec:progressive)

Rationale: Systems-first is the headline contribution that differentiates from micrograd/MiniTorch.
Progressive disclosure becomes the answer to "but won't that overwhelm students?"

🤖 Generated with Claude Code

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-18 12:25:42 -05:00
Vijay Janapa Reddi
12c64efd9c Rewrite introduction with clearer narrative structure and stronger positioning
Academic writer improvements to introduction:
- Strengthen problem statement: algorithms vs systems separation creates workforce gap
- Add concrete evidence: students use loss.backward() without understanding graphs
- Reframe three fundamental questions with evidence-based answers
- Enhance compiler course analogy with specific examples (lexical → parsing → codegen)
- Clarify audience with prerequisites (CS229, fast.ai) and exclusions
- Upgrade pedagogical patterns to 'innovations' with measurable outcomes
- Add concrete metrics: Conv2d 109× efficiency, O(N²) scaling, 4× compression

Key structural changes:
- Paragraph 2: Show the gap with concrete missing knowledge examples
- Paragraph 4: Three questions framework provides clearer narrative arc
- Paragraph 5: Compiler analogy promoted and strengthened
- Paragraph 6: Audience scope tightened with specific prerequisites
- Paragraph 7: Pedagogical innovations with bold emphasis and measurements

Maintains honest scope on empirical validation while strengthening demonstrated contributions.

🤖 Generated with Claude Code

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-18 11:11:56 -05:00
Vijay Janapa Reddi
66ba448e45 Add workforce gap framing to introduction with supporting citations
Reframe introduction to emphasize ML systems engineering workforce shortage as core problem:
- Open with 3.2:1 supply/demand ratio and 150K global practitioners
- Position tacit knowledge (not algorithmic ML) as bottleneck for systems engineering
- Contrast automation of model design vs. manual judgment for memory/performance tradeoffs
- Add workforce citations: Robert Half 2024 talent gap, Keller Executive Search 2025 AI gap

Introduction now grounds TinyTorch's pedagogical approach in workforce development necessity.

🤖 Generated with Claude Code

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-18 10:14:09 -05:00
Vijay Janapa Reddi
d4dcf4f046 Apply all remaining critical fixes: tinygrad citation, NBGrader format, hedging, consistency 2025-11-18 09:39:19 -05:00
Vijay Janapa Reddi
d2145086bb Fix critical factual errors: Perceptron date (1957->1958) and memory calculations 2025-11-18 09:24:24 -05:00
Vijay Janapa Reddi
4bfd32f345 Add energy consumption limitation and restructure future work thematically 2025-11-18 06:31:39 -05:00
Vijay Janapa Reddi
d98ffe3ef1 Restructure milestone and systems sections for clearer flow 2025-11-18 06:29:57 -05:00
Vijay Janapa Reddi
2cbfbd1479 Add Harvard TinyML, clarify bottom-up positioning, standardize code listing captions 2025-11-18 06:27:46 -05:00
Vijay Janapa Reddi
dfa3a6e3bf Define undefined jargon: FLOPs, BPE, KV caching for arXiv accessibility 2025-11-18 05:23:15 -05:00
Vijay Janapa Reddi
19e3288821 Reduce redundancy and improve flow: fix terminology, split dense paragraphs, streamline systems-first messaging 2025-11-18 05:19:13 -05:00
Vijay Janapa Reddi
e71d188d05 Improve abstract clarity and trim verbose content 2025-11-18 05:15:15 -05:00
Vijay Janapa Reddi
11d45d432c Fix technical inaccuracies: Adam memory line 569, convolution complexity consistency, ImageNet calculation 2025-11-18 05:12:35 -05:00
Vijay Janapa Reddi
d62fd12431 Add missing references and improve related work positioning
- Added CS231n, CMU DL Systems, JAX references
- Clarified MiniTorch includes efficiency considerations
- Acknowledged d2l.ai NumPy implementation track
- Positioned TinyTorch relative to university courses
- Fixed mischaracterizations identified by reviewers
2025-11-18 05:05:01 -05:00
Vijay Janapa Reddi
f8de0565ca Refine production language precision in KV caching description 2025-11-18 05:01:50 -05:00
Vijay Janapa Reddi
c245f37923 Fix critical Adam memory factual error
Changed incorrect 3× parameter memory to accurate 2× optimizer state (momentum + variance) = 4× total training memory
2025-11-18 05:01:17 -05:00
Vijay Janapa Reddi
35b5176f3b Redesign paper header with white paper style
- Add orange-red accent bar on left side of header
- Style header with grey text for TinyTorch branding and author name
- Move page numbers to bottom center for cleaner layout
- Add subtle separator line with proper spacing
- Keep first page completely clean with no header
- Adjust header spacing for better visual balance
2025-11-17 13:37:50 -05:00
Vijay Janapa Reddi
936bbeb31c Remove temporary planning documents
Deleted outdated planning and strategy documents:
- paper/SUGGESTED_ADDITIONS.md (temporary paper planning doc)
- docs/development/ temporary planning files (not tracked in git)

Kept active documentation files for testing, module templates, and quick references.
2025-11-17 00:29:38 -05:00
Vijay Janapa Reddi
a13b4f7244 Improve SIGCSE paper with reviewer feedback and clean up repository
Paper improvements:
- Add differentiated time estimates (60-80h experienced, 100-120h typical, 140-180h struggling)
- Moderate cognitive load claims with hedging language and empirical validation notes
- Add ML Systems Research subsection with citations (Baydin AD survey, Chen gradient checkpointing, TVM, FlashAttention)
- Add comprehensive Threats to Validity section (selection bias, single institution, demand characteristics, no control group, maturation, assessment validity)
- Define jargon (monkey-patching) at first use with clear explanation

Documentation updates:
- Restructure TITO CLI docs into dedicated section (overview, modules, milestones, data, troubleshooting)
- Update student workflow guide and quickstart guide
- Remove deprecated files (testing-framework.md, tito-essentials.md)
- Update module template and testing architecture docs

Repository cleanup:
- Remove temporary review files (ADDITIONAL_REVIEWS.md, EDTECH_OPENSOURCE_REVIEWS.md, TA_STRUGGLING_STUDENT_REVIEWS.md, etc.)
- Remove temporary development planning docs
- Update demo GIFs and configurations
2025-11-16 23:46:38 -05:00
Vijay Janapa Reddi
3b70488856 Address reviewer feedback: positioning, scope, and adoption clarity
Conducted multi-perspective review (6 reviewers: undergrad student, CS
professor, industry engineer, PhD student, learning scientist, program
chair). Implemented all high-priority improvements:

1. Added 'Is TinyTorch Right for You?' self-assessment (Section 1.1)
   - When to use vs not use TinyTorch
   - Clear positioning (after CS231n, before advanced systems)
   - Time commitment transparency (60-80 hours)
   - Target audience specification

2. Added 3 concrete course integration models (Section 3.5)
   - Model 1: Standalone 4-credit course (14 weeks)
   - Model 2: Half-semester in existing ML course (7 weeks)
   - Model 3: Optional deep-dive track (self-paced)
   - Instructor resource needs explicitly stated

3. Sharpened abstract contribution framing
   - Changed from 'framework' to 'pedagogical patterns'
   - Emphasized design contribution (not empirical study)
   - Clarified enables educators + researchers

4. Added 'What's NOT Covered' prominently (Section 6.1)
   - GPU/CUDA programming explicitly omitted
   - Distributed training not covered
   - Production deployment/serving excluded
   - Advanced systems techniques listed
   - Clear positioning: foundation, not replacement

5. Verified Adam memory technical precision
   - All mentions already specify '3x parameter memory'
   - Distinction from activation memory clear

Key reviewer themes addressed:
- Positioning ambiguity → Clear when/how to use
- GPU omission concerns → Prominently acknowledged upfront
- Adoption barriers → 3 concrete integration models
- Time investment ROI → Self-assessment + positioning

Paper now targets SIGCSE 2026 design track more clearly.
2025-11-16 21:52:04 -05:00
Vijay Janapa Reddi
492e068f82 Add implementation details from module analysis
Analyzed actual module source code and added key pedagogical features:

Major additions:
- Historical milestone validation system (Section 5.3)
  * 6 milestones recreating 1957-2024 ML breakthroughs
  * Objective correctness validation via historical accuracy
  * Intrinsic motivation through narrative framing
  * Dual purpose: pedagogy + implementation validation

- NBGrader automated assessment infrastructure (Section 5.4)
  * Solution/test cells with grade metadata
  * Point allocation reflects priorities
  * Enables MOOC/large classroom deployment
  * Caveat: unvalidated at scale

- Production package organization (Section 5.5)
  * Modules export to tinytorch.nn.Conv2d API
  * Students build shippable framework, not toy code
  * nbdev integration for professional workflows

- Connection Maps for knowledge integration (Section 5.6)
  * Shows prerequisites, current focus, enabled capabilities
  * Makes expert knowledge structures visible
  * Reduces 'why does this matter' disengagement

Updated abstract to highlight 3 (not 2) novel contributions, adding
historical milestone validation as third major pattern.

Implementation analysis documented in SUGGESTED_ADDITIONS.md for
reference.
2025-11-16 21:33:33 -05:00
Vijay Janapa Reddi
3c4cf573a3 Add research paper: TinyTorch educational framework design
Complete LaTeX source for academic paper on TinyTorch pedagogical approach.

Key contributions:
- Progressive disclosure via monkey-patching
- Systems-first curriculum design
- Historical milestone validation
- Constructionist framework building

Includes 7 sections, 3 tables, 5 code listings, 22 references.
All reviewer feedback incorporated.

Ready for submission to ArXiv, SIGCSE 2026, ICER 2026.
2025-11-16 18:41:23 -05:00