Six Key Innovations Boosting Cryptographic Hardware Performance

To bring tomorrow’s cryptography to life, the industry must blend inventive hardware upgrades with software optimizations that slash compute demands. The good news? We’re building on a solid foundation of proven technologies.

In the near future, encryption will be ubiquitous—from grocery lists to medical records. That promise is exciting, yet the cryptographic landscape remains volatile. Today’s mission is to secure data against threats that will emerge in the coming decade.

Every byte of data may undergo multiple cryptographic operations as it traverses software, network, and storage layers. These layers protect critical business functions but also represent the most compute‑intensive tasks in modern hardware. As data volumes soar and organizations adopt larger key sizes and multi‑algorithm suites, the demand for cryptographic computation continues to rise sharply.

To address this “compute cost” problem, the hardware sector has introduced new microarchitectural enhancements, fixed‑function instruction sets, and software‑level optimizations. A landmark example is the AES‑NI instruction set, which dramatically reduced the CPU cycles required for Advanced Encryption Standard and other FIPS algorithms. Over the last decade, these advances have driven widespread adoption of robust encryption across enterprises.

Quantum computing threatens both symmetric and asymmetric algorithms. While extending key sizes from 128 bits to 256 bits hardens AES against quantum attacks, it also raises compute overhead. Likewise, RSA and ECDSA will likely become obsolete. Rather than a “death by quantum,” the industry is pivoting toward post‑quantum cryptography (PQC) with standards that balance security, key size, storage, and performance. The NIST PQC competition already showcases multiple promising candidates.

The shift to quantum‑resistant algorithms will be gradual; legacy schemes will coexist until the new standards prove both secure and economically viable. Until then, organizations will cautiously adopt stronger encryption only when performance penalties are acceptable.

Below are six transformative innovations that are accelerating tomorrow’s cryptographic capabilities today:

TLS operates in two phases. During session initiation, the client uses a public‑key method (commonly RSA) to exchange a secret key. RSA’s modular exponentiation is computationally expensive, consuming a large share of processor cycles. Combining RSA with Elliptic Curve Cryptography (ECC) and perfect forward secrecy yields stronger security at lower cost.

In the data‑transfer phase, TLS encrypts packets and authenticates them via MACs. Cipher suites like AES‑GCM fuse encryption and authentication, reducing round‑trip latency and simplifying the implementation. Optimized bulk‑data paths in modern CPUs further enhance throughput.

To accelerate big‑number arithmetic, vendors now ship specialized instruction sets. Intel’s Ice Lake processors, for example, support AVX512_INTEGER_FMA (AVX512_IFMA), which multiplies eight 52‑bit unsigned integers in parallel and adds the result to a 64‑bit accumulator. Coupled with multi‑buffer processing, these instructions deliver significant speed‑ups for RSA, ECC, and other public‑key operations.

Two vector‑based extensions boost AES performance: Vectorized AES (VAES) and vectorized carryless multiplication. VAES processes up to four 128‑bit blocks simultaneously using 512‑bit ZMM registers, benefiting all AES modes. The carryless multiply extension speeds Galois hashing, thereby accelerating AES‑GCM.

New SHA extensions accelerate SHA‑256 by executing multiple rounds per instruction. These improvements enable more hashing workloads—critical for integrity checks, key derivation, and blockchain operations—without sacrificing performance.

Introduced in 2010, function stitching merges two traditionally sequential algorithms (e.g., AES‑CBC and SHA‑256) into a single, interleaved routine. By overlapping data dependencies and instruction latencies, the CPU’s execution units stay busy, yielding higher throughput than separate pipelines.

Multi‑buffering runs several independent data streams in parallel. When paired with SIMD (AVX/AVX2/AVX512) instructions, it dramatically improves throughput for hashing and symmetric encryption, even on processors lacking native vector support. As data volumes grow, this technique will be essential to maintain performance.

Quantum computing will arrive sooner than we expect. The industry’s mindset is shifting from “Should we encrypt?” to “Why is this data not encrypted?” By combining hardware advances with algorithmic and software innovations, we can meet the challenges of a post‑quantum world and accelerate the adoption of next‑generation cryptographic schemes.

Wajdi Feghali is an Intel Fellow.

>> This article was originally published on our sister site, EE Times.

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