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Dennard scaling has ended. Lowering the voltage supply (V dd) to sub-volt levels causes intermittent losses in signal integrity, rendering further scaling (down) no longer acceptable as a means to lower the power required by a processor core. However, it is possible to correct the occasional errors caused due to lower V dd in an efficient manner and effectively lower power. By deploying the right amount and kind of redundancy, we can strike a balance between overhead incurred in achieving reliability and energy savings realized by permitting lower V dd. One promising approach is the Redundant Residue Number System (RRNS) representation. Unlike other error correcting codes, RRNS has the important property of being closed under addition, subtraction and multiplication, thus enabling computational error correction at a fraction of an overhead compared to conventional approaches. We use the RRNS scheme to design a Computationally-Redundant, Energy-Efficient core, including the microarchitecture, Instruction Set Architecture (ISA) and RRNS centered algorithms. From This paper is an extension of "Computationally-Redundant Energy-Efficient Processing for Y'all (CREEPY)" [11]. This submission adds the following: (1) Correction factor analysis for RRNS signed arithmetic, including an improved correction factor computation for signed multiplication via an LUT based mechanism. (Section 4.8.5) (2) Design and evaluation of an efficient RRNS multiplier unit by using the index-sum technique, along with associated re-derivation of suitable RRNS bases. (Sections 4.4 and 4.5) (3) A novel adaptive check insertion strategy that leverages hardware/software runtime or compiler. (Section 4.6.3) (4) Impact of multi-domain voltage supply to further lower energy consumption. (Sections 4.7, 6.1 and 6.3) (5) Improved evaluation accuracy by simulating an LLC-main memory hierarchy instead of a perfect cache. (Section 5) (6) Energy limit analysis for binary, RNS and RRNS cores. (Section 6) These add significantly more than 30% new material and provide greater insight into RRNS core design. W.r.t. written content, every section has been revamped to better present the new findings above.

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