Low-area energy-efficient security primitives are key building blocks for enabling end-to-end content protection, user authentication in IoT platforms. This paper describes 3 designs that employ energy-efficient circuit techniques with optimal hardware-friendly arithmetic for seamless integration into area/battery constrained IoT systems: 1) A 2040-gate AES accelerator achieving 289Gbps/W efficiency in 22nm CMOS, 2) Hardened hybrid Physically Unclonable Function (PUF) circuit to generate a 100% stable encryption key. 3) All-digital TRNG to achieve >0.99 min-entropy with 3pJ/bit energy-efficiency.

Low-area energy-efficient security primitives are key building blocks for enabling end-to-end content protection, user authentication in IoT platforms. This paper describes 3 designs that employ energy-efficient circuit techniques with optimal hardware-friendly arithmetic for seamless integration into area/battery constrained IoT systems: 1) A 2040-gate AES accelerator achieving 289Gbps/W efficiency in 22nm CMOS, 2) Hardened hybrid Physically Unclonable Function (PUF) circuit to generate a 100% stable encryption key. 3) All-digital TRNG to achieve >0.99 min-entropy with 3pJ/bit energy-efficiency.

Low-area energy-efficient security primitives are key building blocks for enabling end-to-end content protection, user authentication, and consumer confidentiality in the IoT world that is estimated to surpass 50billion smart and connected devices by 2020. This paper describes design approaches that blend energy-efficient circuit techniques with optimal accelerator microarchitecture datapath, and hardware friendly arithmetic to achieve ultra-low energy consumption in security platforms for seamless adoption in area/battery constrained and self-powered systems. Industry leading energy-efficiency is demonstrated with three designs, fabricated and measured in advanced process technologies: 1) A 2040-gate arithmetically optimized composite-field Sbox based AES accelerator achieves 289Gbps/W peak energy-efficiency while offering 432Mbps throughput in 22nm tri-gate CMOS, 2) Hybrid Physically Unclonable Function (PUF) circuit leverages burn-in induced aging to reduce bit-error, followed by temporal-majority-voting, dark-bit masking, and error-correction conditioning techniques to generate a 100% stable full-entropy key with 190fJ/bit energy consumption in 22nm tri-gate CMOS. 3) A light-weight all digital TRNG uses in-line correlation suppressor and entropy-extractor circuits to achieve >0.99 min-entropy with 3pJ/bit measured energy-efficiency while operating down to 300mV in 14nm tri-gate CMOS.

Multiple networks have been used in several processor implementations to scale bandwidth and ensure protocol-level deadlock freedom for different message classes. In this paper, we observe that a multiple-network design is also attractive from a power perspective and can be leveraged to achieve energy proportionality by effective power gating.

With multi-core processors now mainstream, the shift to many-core processors poses a new set of design challenges. In particular, the scalability of coherence protocols remains a significant challenge. While complex Network-on-Chip interconnect fabrics have been proposed and in some cases implemented, most of industry has slowly evolved existing coherence solutions to meet the needs of a growing number of cores. Industries' slow adoption of Network-on-Chip designs is in large part due to the significant effort needed to design and verify the system. However, simply scaling bus-based coherence is not straightforward either because of increased contention and latency on the bus for large core counts.

A scalable architecture to design high radix switch fabric is presented. It uses circuit techniques to re-use existing input and output data buses and switching logic for fabric configuration and supporting multiple arbitration policies. In addition, it integrates a 4-level message-based priority arbitration for quality of service. Fine grain clock gating, tiled fabric topology and self-regenerating bit-line repeaters enable scaling the router to 8k wires. A 64x64(128b data) switch fabric fabricated in 45nm SOI CMOS spans 4.06mm2 and achieves a throughput of 4.5Tb/s at 3.4Tb/s/W at 1.1V with a peak measured efficiency of 7.4Tb/s/W at 0.6V.

Driven by continued scaling of Moore's Law, the number of processing elements on a die are increasing dramatically. Recently there has been a surge of wide single instruction multiple data architectures designed to handle computationally intensive applications like 3D graphics, high definition video, image processing, and wireless communication. A limit of the SIMD width of these types of architectures is the scalability of the interconnect network between the processing elements in terms of both area and power. To mitigate this problem, we propose the use of a new interconnect topology, XRAM, which is a low power high performance matrix style crossbar. It re-uses output buses for control programming, and stores multiple swizzle configurations at the cross points using SRAM cells, significantly reducing routing congestion and control signaling. We show that compared to conventionally implemented crossbars, the area scales with the product of inputx output ports while consuming almost 50% less energy. We present an application case study, color-space conversion, utilizing XRAM and show a 1.4× gain in performance while consuming 1.5-2.5× less power.