Microprocessors

A 28-nm 18.7 TOPS/mm $^2$ 89.4-to-234.6 TOPS/W 8b Single-Finger eDRAM Compute-in-Memory Macro With Bit-Wise Sparsity Aware and Kernel-Wise Weight Update/Refresh

A 28-nm 18.7 TOPS/mm $^2$ 89.4-to-234.6 TOPS/W 8b Single-Finger eDRAM Compute-in-Memory Macro With Bit-Wise Sparsity Aware and Kernel-Wise Weight Update/Refresh 150 150

Abstract:

This article reports a high-density 3T1C single-finger (SF) embedded dynamic random access memory (eDRAM) compute-in-memory (CIM) macro. It features several techniques that enhance the memory density, the energy efficiency, and the throughput density, namely: 1) a high-density 3T1C SF-eDRAM cell with low-leakage retention (LLR) to improve the memory density …

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EMBER: Efficient Multiple-Bits-Per-Cell Embedded RRAM Macro for High-Density Digital Storage

EMBER: Efficient Multiple-Bits-Per-Cell Embedded RRAM Macro for High-Density Digital Storage 150 150

Abstract:

Designing compact and energy-efficient resistive RAM (RRAM) macros is challenging due to: 1) large read/write circuits that decrease storage density; 2) low-conductance cells that increase read latency; and 3) the pronounced effects of routing parasitics on high-conductance cell read energy. Multiple-bits-per-cell RRAM can boost storage density but has further challenges resulting from …

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A 28-nm 64-kb 31.6-TFLOPS/W Digital-Domain Floating-Point-Computing-Unit and Double-Bit 6T-SRAM Computing-in-Memory Macro for Floating-Point CNNs

A 28-nm 64-kb 31.6-TFLOPS/W Digital-Domain Floating-Point-Computing-Unit and Double-Bit 6T-SRAM Computing-in-Memory Macro for Floating-Point CNNs 150 150

Abstract:

With the rapid advancement of artificial intelligence (AI), computing-in-memory (CIM) structure is proposed to improve energy efficiency (EF). However, previous CIMs often rely on INT8 data types, which pose challenges when addressing more complex networks, larger datasets, and increasingly intricate tasks. This work presents a double-bit 6T static random-access memory (…

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