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<!DOCTYPE html>
<html lang="en" data-theme="dark">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Cryptography Primitives Acceleration (CPA) Tutorial</title>
<meta name="description" content="ASPLOS Tutorial on Cryptography Primitives Acceleration (CPA).">
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<h3 class="nav-title">tutorial</h3>
<ul class="nav-links">
<li><a href="index.html" class="active">ASPLOS'26@Pittsburgh</a></li>
</ul>
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<div class="nav-section">
<h3 class="nav-title">docs</h3>
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<li><a href="beginner.html">Easy HE Background</a></li>
<li><a href="cross.html">CROSS</a></li>
<li><a href="tpu.html">TPU Novice to Master</a></li>
<li><a href="ntt.html">NTT Algorithms</a></li>
<li><a href="open_challenge.html">Open Challenge</a></li>
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<!-- Hero / Abstract Section -->
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<h1>Cryptography Primitives Acceleration (CPA Tutorial)</h1>
<p class="subtitle"><span class="gradient-text">Mar 22: Morning @ ASPLOS'26</span></p>
<div class="text-block">
<p>Artificial Intelligence (AI) is driving a new industrial revolution, transforming how we create,
exchange, and safeguard information. From chatbots and autonomous vehicles to enterprise assistants and
AI coders, human workflows are increasingly translated into digital tokens—a process that <strong>makes
the world effectively tokenized</strong>. Yet this transformation exposes sensitive data at an
unprecedented scale, making privacy preservation a defining challenge of the AI era. Current privacy
solutions, however, remain prohibitively expensive. Software-based encryption can slow computation by
100–10,000×, while hardware isolation demands millions of dollar fabrication costs. These barriers make
privacy protection over prohibitive, leaving the broader AI revolution unprotected. This tutorial gives
you a tour of the state-of-the-art in cryptography primitives acceleration, and how to make privacy
protection as efficient and accessible as unprotected AI. </p>
<p>In this tutorial, you will learn:</p>
<ul>
<li><strong>(a)</strong> How to convert an AI model into Homomorphic Encryption (HE), enabling
privacy-preserving AI inference, and how to make a compiler to do so?</li>
<li><strong>(b)</strong> How to deploy HE on TPU hardware to achieve SotA throughput and energy
efficiency?</li>
<li><strong>(c)</strong> How to further extend HE to arbitrary-precision cryptography primitives,
enabling Zero-Knowledge Proofs (ZKPs)?</li>
<li><strong>(d)</strong> How to write high-performance JAX kernels, optimize them to run on distributed
TPUs?</li>
</ul>
</div>
<!-- Overarching figure placeholder -->
<div class="figure-placeholder">
<img src="fig/cpa_overview.png" alt="Overarching Figure of the Repository" class="repo-figure">
<p class="caption">Figure 1: CPA overview, turning TPU as a crypto accelerator, achieving SoTA
throughput and energy efficiency.</p>
</div>
</section>
<!-- Resources Section -->
<section id="resources">
<h2>CPA Resources</h2>
<div class="resources-grid">
<a href="https://github.com/EfficientPPML/CROSS" target="_blank" class="resource-card">
<h3>CROSS</h3>
<p>Enabling Google TPUs for HE, achieving SoTA throughput and energy efficiency.</p>
</a>
<a href="https://github.com/google/heir" target="_blank" class="resource-card">
<h3>HEIR</h3>
<p>Google's MLIR-based compiler toolchain for converting AI models into HE.</p>
</a>
<a href="https://github.com/EfficientPPML/SmartPAF" target="_blank" class="resource-card">
<h3>SmartPAF</h3>
<p>Non-polynomial operators approximations to make model crypto-friendly.</p>
</a>
<a href="https://github.com/EfficientPPML/MORPH" target="_blank" class="resource-card">
<h3>MORPH</h3>
<p>Enabling TPUs for ZKP (arbitrary-precision MSM and NTT).</p>
</a>
<a href="" target="_blank" class="resource-card">
<h3>Encrypted Computing SDK</h3>
<p>Stay tuned for latest repository of Encrypted Computing SDK.</p>
</a>
</div>
</section>
<!-- Keynote Speaker Section -->
<section id="keynote">
<h2>Keynote Speaker</h2>
<div class="keynote-card">
<div class="keynote-header">
<div class="keynote-photo">
<img src="fig/craig_gentry.jpg" alt="Craig Gentry">
</div>
<div class="keynote-intro">
<h3><a href="https://en.wikipedia.org/wiki/Craig_Gentry_(computer_scientist)" target="_blank">Craig Gentry</a></h3>
<p class="keynote-affiliation">Chief Scientist, Cornami</p>
<p class="keynote-bio">Craig Gentry is known for constructing the first fully homomorphic encryption scheme in 2009, resolving a central open problem in cryptography. His subsequent work has focused on improving the efficiency of FHE and related cryptographic primitives including obfuscation and multilinear maps. He received the <strong>ACM Grace Murray Hopper Award</strong> and the <strong>Gödel Prize</strong> for his work on FHE.</p>
</div>
</div>
<div class="keynote-talk">
<h4>Practical FHE: Three Questions for the Architecture Community</h4>
<div class="keynote-abstract">
<p>Fully homomorphic encryption allows arbitrary computation on encrypted data without relying on trusted hardware — a property that becomes increasingly valuable as AI drives sensitive computation onto outsourced infrastructure. This talk examines three questions that arise naturally when the architecture community turns its attention to FHE:</p>
<ul>
<li><strong>How bad is the overhead?</strong> Perhaps less than you think. For matrix multiplication — the operation dominating transformer inference — recent "inside-out" techniques reduce encrypted MM to a small constant number of unencrypted matrix multiplications, allowing use of standard optimized routines (cuBLAS, MXU kernels, etc.).</li>
<li><strong>What should hardware target?</strong> FHE workloads are fully deterministic, streaming-friendly, and built on structured algebra — excellent properties for hardware acceleration. But perhaps the safest bets are on FHE's invariant structural properties, not on whichever operation happens to be the current bottleneck.</li>
<li><strong>Is this even an ASIC problem?</strong> Commodity GPUs and TPUs already provide strong baselines. While ASICs can accelerate FHE computation, Amdahl's Law limits overall speedup when data movement and memory bandwidth are also significant factors.</li>
</ul>
<p>The talk concludes by asking why FHE is not ubiquitous despite growing demand, and argues that algorithms, hardware, and systems need modular interfaces across the full stack that let each layer advance without breaking the others.</p>
</div>
</div>
</div>
</section>
<!-- Schedule Section -->
<section id="schedule">
<h2>Agenda (Mar 22, 2026, ASPLOS'26)</h2>
<div class="timeline">
<div class="timeline-item">
<div class="time">9:00 AM ~ 9:05 AM</div>
<div class="content">
<h3>Welcome</h3>
<p class="speaker">Speaker: <a href="https://tusharkrishna.ece.gatech.edu/" target="_blank">Tushar Krishna</a></p>
</div>
</div>
<div class="timeline-item">
<div class="time">9:05 AM ~ 9:50 AM</div>
<div class="content">
<h3>Keynote: Practical FHE: Three Questions for the Architecture Community</h3>
<p class="speaker">Speaker: <a href="https://en.wikipedia.org/wiki/Craig_Gentry_(computer_scientist)" target="_blank">Craig Gentry</a></p>
<div class="talk-recordings">
<a href="https://youtu.be/E3mT3iIpPDE" target="_blank" class="talk-video">
<span class="play-icon"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M8 5v14l11-7z"/></svg></span>
Watch Recording (Part 1)
</a>
</div>
</div>
</div>
<!-- <div class="timeline-item">
<div class="time">9:50 AM ~ 10:00 AM</div>
<div class="content">
<h3>Introduction to Verifiable Privacy-preserving AI via HE and ZKP</h3>
<p class="speaker">Speaker: <a href="https://jianmingtong.github.io/" target="_blank">Jianming Tong</a></p>
</div>
</div> -->
<div class="timeline-item">
<div class="time">9:50 AM ~ 10:20 AM</div>
<div class="content">
<h3>HEIR Compiler: A Universal Compiler for Homomorphic Encryption</h3>
<p class="speaker">Speaker: <a href="https://www.jeremykun.com/" target="_blank">Jeremy Kun</a></p>
<ul>
<li> Compilation of a PyTorch model through the HEIR compiler.</li>
<li> Optimization passes and design choices in HEIR compiler.</li>
<li> Highlight potential for external projects to integrate with HEIR.</li>
<li> Doing research on top of HEIR, and new directions for research.</li>
</ul>
<div class="talk-recordings">
<a href="https://youtu.be/N2wBpT40bYA" target="_blank" class="talk-video">
<span class="play-icon"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M8 5v14l11-7z"/></svg></span>
Watch Recording (Part 2)
</a>
</div>
<!-- <ul>
<li>Overview of components for compiling ML models</li>
<li><strong>Hands on:</strong> Model rearchitecture</li>
<li><strong>Hands on:</strong> Arithmetization (polynomial approximation, packing/kernel selection)
</li>
<li><strong>Hands on:</strong> Scheme selection, noise analysis, ciphertext management</li>
<li><strong>Hands on:</strong> Accuracy degradation considerations</li>
<li><strong>Hands on:</strong> Differences among schemes (CGGI, CKKS/BGV/BFV)</li>
<li><strong>Hands on:</strong> Life cycle of model compilation using CKKS</li>
<li><strong>Hands on:</strong> Export to jaxite (CROSS)</li>
</ul> -->
</div>
</div>
<div class="timeline-item">
<div class="time">10:20 PM ~ 10:35 PM</div>
<div class="content">
<h3>A new suite for FHE Benchmarking</h3>
<p class="speaker">Speaker: <a href="https://www.linkedin.com/in/shruthigorantala/" target="_blank">Shruthi Gorantala</a></p>
<ul>
<li>Introduction to fhe-benchmarking.org</li>
<li>Design choices for the framework</li>
<li>How to make a submission</li>
<li>How to add new workloads</li>
</ul>
<div class="talk-recordings">
<a href="https://youtu.be/0kDqCjDq9iQ" target="_blank" class="talk-video">
<span class="play-icon"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M8 5v14l11-7z"/></svg></span>
Watch Recording (Part 3)
</a>
</div>
</div>
</div>
<div class="timeline-break">
<span>Break (10:35 AM ~ 11:00 AM)</span>
</div>
<div class="timeline-item">
<div class="time">11:00 AM ~ 11:35 AM</div>
<div class="content">
<h3>CROSS – Enabling Google TPU for Homomorphic Encryption</h3>
<p class="speaker">Speaker: <a href="https://jianmingtong.github.io/" target="_blank">Jianming Tong</a></p>
<p>Compilation Transformation Turning TPU into SoTA Throughput Machine for HE Operators.</p>
<ul>
<li>TPU Detailed Architecture and Programming Tips.</li>
<li>Memory, Computation and Accuracy overhead of Cryptography primitives (HE and ZKP).</li>
<li>Gap between TPU and HE.</li>
<li>Basis Aligned Transformation (BAT) and Memory Aligned Transformation (MAT).</li>
<li><strong>Hands on:</strong> HE Kernels (HEAdd, HEMul, HERotation, HERescale, NTT, Keyswitch)</li>
<li><strong>Hands on:</strong> Encode, Encryption, Decryption, Decode</li>
<!-- <li><strong>Hands on:</strong> Parameter Selection (32-bit logq, extended via rescaling)</li>
<li><strong>Hands on:</strong> MNIST inference benchmark</li>
<li><strong>Hands on:</strong> Similarity search benchmark</li> -->
</ul>
<div class="talk-recordings">
<a href="https://youtu.be/ihjsN5UPN84" target="_blank" class="talk-video">
<span class="play-icon"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M8 5v14l11-7z"/></svg></span>
Watch Talk (Part 4a)
</a>
<a href="https://youtu.be/7Mv6HjpR3gI" target="_blank" class="talk-video">
<span class="play-icon"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M8 5v14l11-7z"/></svg></span>
Hands-on Q&A (Part 4b)
</a>
</div>
</div>
</div>
<div class="timeline-item">
<div class="time">11:35 AM ~ 11:50 PM</div>
<div class="content">
<h3>MORPH – Enabling Google TPU for ZKP</h3>
<p class="speaker">Speaker: <a href="https://scholar.google.com/citations?user=e5yfa28AAAAJ&hl=en" target="_blank">Jingtian Dang</a></p>
<p>Compilation Transformation Turning TPU into SoTA Throughput Machine for ZKP.</p>
<ul>
<li>MXU-lazy Modular Reduction for High-precision Modular Arithmetics.</li>
<li><strong>Hands on:</strong> Efficient Modular Reduction and Multiplication for Big Integers (>256
bits)</li>
<li><strong>Hands on:</strong> High-precision MSM and NTT</li>
</ul>
<div class="talk-recordings">
<a href="https://youtu.be/5CGYk3I3NXg" target="_blank" class="talk-video">
<span class="play-icon"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M8 5v14l11-7z"/></svg></span>
Watch Recording (Part 5)
</a>
</div>
</div>
</div>
<div class="timeline-item">
<div class="time">11:50 PM ~ 12:20 PM</div>
<div class="content">
<h3>Hardware-Software co-design for advanced hardware accelerators</h3>
<p class="speaker">Speaker: <a href="https://sites.google.com/site/anupamgolder09/" target="_blank">Flavio Bergamaschi</a></p>
<ul>
<li>High-level overview of a photonics-based compute core </li>
<li>High-level overview of the Encrypted Computing SDK</li>
<li>Introduction to the Polynomial Instruction Set Architecture</li>
<li>Introduction to Kernel generation</li>
<li>Introduction to local and global optimizations</li>
<li>Examples of compiled kernels for FHE ciphertext maintenance (e.g., Relinearization and Modulus switching)</li>
</ul>
<div class="talk-recordings">
<a href="https://youtu.be/WK5NuaXidk0" target="_blank" class="talk-video">
<span class="play-icon"><svg viewBox="0 0 24 24" fill="currentColor" aria-hidden="true"><path d="M8 5v14l11-7z"/></svg></span>
Watch Recording (Part 6)
</a>
</div>
</div>
</div>
</div>
</section>
<!-- Organizers Section -->
<section id="organizers">
<h2>Organizers</h2>
<div class="organizers-grid">
<!-- Jianming Tong -->
<a href="https://jianmingtong.github.io/" target="_blank" class="organizer-card">
<div class="photo-placeholder">
<img src="fig/jianming_sm.png" alt="Jianming Tong">
</div>
<h3>Jianming Tong</h3>
<p class="affiliation">Georgia Institute of Technology</p>
<p class="bio">5th-year PhD candidate, enabling systems for Agentic Cryptography.
One system for both AI and cryptography primitives.</p>
</a>
<!-- Tushar Krishna -->
<a href="https://tusharkrishna.ece.gatech.edu/" target="_blank" class="organizer-card">
<div class="photo-placeholder"><img src="fig/tushar.png" alt="Tushar Krishna"></div>
<h3>Tushar Krishna</h3>
<p class="affiliation">Georgia Institute of Technology</p>
<p class="bio">Associate Professor in ECE. Research spans computer architecture, interconnection
networks, distributed systems, and AI/ML accelerator systems.</p>
</a>
<!-- Jeremy Kun -->
<a href="https://www.jeremykun.com/" target="_blank" class="organizer-card">
<div class="photo-placeholder"><img src="fig/jeremy.jpg" alt="Jeremy Kun"></div>
<h3>Jeremy Kun</h3>
<p class="affiliation">Google</p>
<p class="bio">Staff software engineer and tech lead on HEIR compiler. Author of "A Programmer's
Introduction to Mathematics".</p>
</a>
<!-- Flavio Bergamaschi -->
<a href="https://sites.google.com/site/anupamgolder09/" target="_blank" class="organizer-card">
<div class="photo-placeholder"><img src="fig/Flavio.jpg" alt="Flavio Bergamaschi"></div>
<h3>Flavio Bergamaschi</h3>
<p class="affiliation">Optalysys Ltd</p>
<p class="bio">Vice President of Cryptography and Algorithms at Optalysys, responsible for shaping the research and development strategy and the hardware-software co-design of Optalysys' Photonic Technology.
</p>
</a>
<!-- Anupam Golder -->
<a href="https://sites.google.com/site/anupamgolder09/" target="_blank" class="organizer-card">
<div class="photo-placeholder"><img src="fig/anupam.jpeg" alt="Anupam Golder"></div>
<h3>Anupam Golder</h3>
<p class="affiliation">Intel Corporation</p>
<p class="bio">Research scientist at Intel CRL developing ASIC microarchitectures for cryptographic
accelerators like FHE.</p>
</a>
<!-- Jingtian Dang -->
<a href="https://scholar.google.com/citations?user=e5yfa28AAAAJ&hl=en" target="_blank"
class="organizer-card">
<div class="photo-placeholder"><img src="fig/jingtian.jpeg" alt="Jingtian Dang"></div>
<h3>Jingtian Dang</h3>
<p class="affiliation">Georgia Institute of Technology</p>
<p class="bio">2nd-year PhD student. Leads the project to map ZKP primitives onto
Google TPUs.</p>
</a>
<!-- Shruthi Gorantala -->
<a href="https://www.linkedin.com/in/shruthigorantala/" target="_blank" class="organizer-card">
<div class="photo-placeholder"><img src="fig/shruthi.jpeg" alt="Shruthi Gorantala"></div>
<h3>Shruthi Gorantala</h3>
<p class="affiliation">Google</p>
<p class="bio">Co-founder of FHE team at Google. Driving standardization of FHE Benchmarks
</p>
</a>
<!-- Asra Ali -->
<a href="https://x.com/AsraEntr0py" target="_blank" class="organizer-card">
<div class="photo-placeholder"><img src="fig/asra.jpg" alt="Asra Ali"></div>
<h3>Asra Ali</h3>
<p class="affiliation">Google</p>
<p class="bio">Software Engineer on Privacy, Safety, and Security. Focus on developing a transpiler for
FHE.</p>
</a>
<!-- Baiyu Li -->
<a href="https://baiyuli.net/" target="_blank" class="organizer-card">
<div class="photo-placeholder"><img src="fig/baiyu.png" alt="Baiyu Li"></div>
<h3>Baiyu Li</h3>
<p class="affiliation">Google</p>
<p class="bio">Research Scientist studying lattice-based cryptography and secure computation. PhD from
UC San Diego.</p>
</a>
<!-- Simon Langowski -->
<a href="https://www.linkedin.com/in/simon-langowski/" target="_blank" class="organizer-card">
<div class="photo-placeholder"><img src="fig/simon.png" alt="Simon Langowski"></div>
<h3>Simon Langowski</h3>
<p class="affiliation">MIT</p>
<p class="bio">PhD student at MIT working on cryptography for systems to innovate efficient algorithms
for crypto workloads.</p>
</a>
</div>
</section>
<!-- Citation Section -->
<section id="citation" class="citation-section">
<h2>Citation</h2>
<p>If you find this tutorial helpful, feel free to:</p>
<ul>
<li>Star CROSS repo at <a
href="https://github.com/EfficientPPML/CROSS">https://github.com/EfficientPPML/CROSS</a></li>
<li>Star the HEIR repo at <a href="https://github.com/google/heir">https://github.com/google/heir</a></li>
<li>Star the Jaxite repo at <a
href="https://github.com/google/jaxite">https://github.com/google/jaxite</a></li>
<li>Cite our paper with biblatex below:</li>
</ul>
<pre><code>@inproceedings{tong2026CROSS,
author = {Jianming Tong and Tianhao Huang and Jingtian Dang and Leo de Castro and Anirudh Itagi and Anupam
Golder and Asra Ali and Jevin Jiang and Jeremy Kun and Arvind and G. Edward Suh and Tushar Krishna},
title = {Leveraging ASIC AI Chips for Homomorphic Encryption},
year = {2026},
address = {Australia},
booktitle = {2026 IEEE International Symposium on High Performance Computer Architecture (HPCA)},
keywords = {AI ASICs, TPU, Fully Homomorphic Encryption},
location = {Australia},
series = {HPCA'26} }</code></pre>
<pre><code>@inproceedings{tong2026MORPH,
author = {Jianming Tong and Jingtian Dang and Simon Langowski and Tianhao Huang and Asra Ali and Jeremy Kun and Srini Devadas and Tushar Krishna},
title = {MORPH: Enabling AI ASICs for Zero Knowledge Proof},
year = {2026},
publisher = {IEEE Press},
booktitle = {Proceedings of the 63nd Annual ACM/IEEE Design Automation Conference},
location = {Los Angeles, California, United States},
series = {DAC '26}
}</code></pre>
<pre><code>@misc{ali2025heiruniversalcompilerhomomorphic,
title={HEIR: A Universal Compiler for Homomorphic Encryption},
author={Asra Ali and Jaeho Choi and Bryant Gipson and Shruthi Gorantala and Jeremy Kun and Wouter Legiest and Lawrence Lim and Alexander Viand and Meron Zerihun Demissie and Hongren Zheng},
year={2025},
eprint={2508.11095},
archivePrefix={arXiv},
primaryClass={cs.CR},
url={https://arxiv.org/abs/2508.11095},
}</code></pre>
</section>
</article>
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<h4>On this page</h4>
<ul>
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