An Efficient Low Power Sparse Clustered Network By Using Reordered Overlapped Content Addressable Memory

نویسندگان

  • S. Muthukrishnan
  • A. Sundram
  • T. Janani
چکیده

A reordered overlapped search mechanism for high-throughput low-energy contentaddressable memories (CAMs). Most mismatches can be found by searching a few bits of a search word. To lower power dissipation, a word circuit is often divided into two sections that are sequentially searched or even pipelined. Because of this process, most of match lines in the second section are unused. Since searching the last few bits is very fast compared to searching the rest of the bits, to increase throughput by asynchronously initiatingsecond-stage searches on the unused match lines as soon as afirststage search is complete. In our circuit implementation, eachword circuit is independently controlled by a locally generated timing signal rather than a global signal. This allows the circuits to be in the required phase for their own local operation: evaluateor precharge, instead of having to synchronize their phase to therest of the word circuits, which greatly reduces the cycle time.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Survey on Content Addressable Memory and Sparse Clustered Network

Most memory devices store and retrieve data by addressing specific memory locations. As a result, this path often becomes the limiting factor for systems that rely on fast memory accesses. The time required to find an item stored in memory can be reduced considerably if the item can be identified for access by its content rather than by its address. A memory that is accessed in this way is call...

متن کامل

Content Addressable Memory Using XNOR CAM Cell

One of the special types of Computer Memory is said to be as Content Addressable Memory. It is also called as associative array or associative storage, associative memory which can be frequently used in very high speed searching applications such as databases, associative computing, lookup tables and networking. CAM is one type of functional memory which contains huge amount of stored data wher...

متن کامل

Sparse Matrix Multiplication on CAM Based Accelerator

Sparse matrix multiplication is an important component of linear algebra computations. In this paper, an architecture based on Content Addressable Memory (CAM) and Resistive Content Addressable Memory (ReCAM) is proposed for accelerating sparse matrix by sparse vector and matrix multiplication in CSR format. Using functional simulation, we show that the proposed ReCAM-based accelerator exhibits...

متن کامل

Associative content-addressable networks with exponentially many robust stable states

The brain must robustly store a large number of memories, corresponding to the many events and scenes a person encounters over a lifetime. However, the number of memory states in existing neural network models either grows weakly with network size or recall performance fails catastrophically with vanishingly little noise. Here we show that it is possible to construct an associative content-addr...

متن کامل

An Adaptive Sparse Distributed Memory

Sparse Distributed Memory is a content addressable, associative memory terhnique which relies on close memory items tending to be clustered together, with some abstraction and blurring of details. This paper discusses the limitations of the original model. Then, we propose a method which improve Sparse Distributed Memory efficiency through an adaptive threshold. The results obtained are good an...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2016