Memory

Data is the most valuable resource in today’s digital economy. Currently over 2.5 quintillion (1018) bytes of data are generated daily and the pace is accelerating. More data than ever needs to be processed. Memory plays a key role in the flow of data. The gap between logic and memory is a bottle neck to system performance. To optimize the trade-off between cost and performance, a hierarchical memory system has been adopted. At the top of the hierarchy are static random access memories (SRAM) and dynamic random access memory (DRAM), both inherently volatile. SRAM is integrated right on the logic chips as cache memory to provide fastest access. DRAM is physically smaller than SRAM and consequently supports higher capacity. DRAM is generally an off-chip memory solution and ~10x slower than SRAM due to the need for constant refresh. Non-volatile memories (NVM) such as Flash are next in the hierarchy providing much higher memory capacity and density while also preserving information in the absence of power.

Recent new technologies are emerging rapidly to bring processing tasks near to or inside the memory to improve computing efficiency and enable new functionalities. Emerging NVMs use new types of materials and mechanisms to store data. They are promising for blending the memory hierarchy to boost the overall performance. Furthermore, their unique characteristics offer great potential to enable new applications (e.g. neuromorphic computing) and novel architectures (e.g. 3D integration).

TSMC’s non-volatile memory solutions include Flash, Spin-transfer torque magnetic random access memory (STT-MRAM), and resistive random access memory (RRAM). TSMC is also actively exploring phase change random access memory (PCRAM), and spin-orbit torque MRAM (SOT-MRAM) elements, as well as selector devices which are essential to support higher density cross-point array architectures.

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  • A 28nm Integrated True Random Number Generator Harvesting Entropy from MRAM

    2018
    This paper presents an integrated True Random Number Generator (TRNG) based on the random switching behavior of Magnetic Tunnel Junctions (MTJs) under low write current. A complete TRNG is designed with minimal overhead to an existing embedded MRAM in 28nm CMOS. To the best of our knowledge, this is the first experimental study of this random process and the first TRNG implemented with commercial STT-MRAM technology. The prototype adds only 180μm 2 to a standard MRAM array for TRNG operation. It passes all NIST randomness tests across -25 to 100°C, while consuming 18pJ/bit with 66Mbps throughput at the nominal condition.
  • Recent Progress and Next Directions for Embedded MRAM Technology

    2018
    MRAM can play a variety of on-chip memory roles in advanced VLSI technology spanning from high retention, solder-reflow-capable non-volatile memory (NVM) to dense non-volatile or high retention working RAMs. This paper describes results for a solder-reflow-capable MRAM NVM and for extensions that trade off high retention against speed, power, and density.
  • A 40nm Low-Power Logic Compatible Phase Change Memory Technology

    2018
    An embedded phase change memory technology in 40nm low-power logic platform is demonstrated with minimal added process complexity - two non-critical additional masks over standard logic. Specially designed hard mask and etching process was used to achieve 50% shrinkage of the memory cell bottom electrode dimension with same lithography tooling as the 40nm logic platform. Bottom electrode CD shrinkage along with optimization of the electrode materials in terms of electrical and thermal conductivity enabled significant (~4x) write current reduction attaining competitive levels of ~300 A at 40nm BE CD. Embedded PCM cells reported in this work demonstrated over 100x memory window - (RESET/SET resistance switching ratio), over 200k cycling endurance with extrapolated 10 year retention at 120 . In this work not only large switching resistance ratios but also highly-controllable resistance values that are almost independent of the PCM starting resistance state are presented along with the corresponding programing pulse requirements. The switching resistance ratio and resistance value controllability are key features for neural network and compute-in-memory applications. In this work, their benefits on design margins for energy efficient high-density binary neural network for inference applications aiming accuracy levels of well over 90% is asserted over an MNIST dataset.
  • A Logic-Compatible Low Power 1T1R PCRAM with Spacer Assisted Process and Multilevel Storage Capabilities

  • Observation of PCRAM Endurance Cycling Induced Porous GST Material

  • Large and Robust Charge-to-Spin Conversion in Sputtered Weyl Semimetal WTex with Structural Disorder

    Topological insulators have recently shown great promise for ultralow-power spin-orbit torque (SOT) devices thanks to their large charge-to-spin conversion efficiency originating from the spin-momentum-locked surface states. Weyl semimetals, on the other hand, may be more desirable due to their spin-polarized surface as well as bulk states, robustness against magnetic and structural disorder, and higher electrical conductivity for integration in metallic magnetic tunnel junctions. Here, we report that sputtered WTex thin films exhibit local atomic and chemical structures of Weyl semimetal WTe2 and host massless Weyl fermions in the presence of structural disorder at low temperatures. Remarkably, we find superior spin Hall conductivity and charge-to-spin conversion efficiency in these sputtered WTex films compared with crystalline WTe2 flakes. Besides, the strength of unidirectional spin Hall magnetoresistance in annealed WTex/Mo/CoFeB heterostructure is up to 20 times larger than typical SOT/ferromagnet bilayers reported at room temperature. We further demonstrate room temperature field-free magnetization switching at a current density as low as 0.97 MA/cm2. These large charge-to-spin conversion properties that are robust in the presence of structural disorder and thermal annealing pave the way for industrial production of Weyl semimetals. Our results open up a new class of sputtered Weyl semimetals for memory and computing based on magnetic tunnel junctions as well as broader planar heterostructures containing SOT/ferromagnet interfaces.
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