International audienceThis paper presents a new methodology for automating the Computational SRAM (C-SRAM) design based on off-the-shelf memory compilers and a configurable RTL IP. The main goal is to drastically reduce the development effort compared to a full-custom design, while offering a flexibility of use and a high-yield production. The proposed C-SRAM architecture has been developed to process energy-efficient vector data coupled with a scalar processor, while limiting the data transfer on the system bus. The results obtained by post P&R simulations show that 2RW and 4RW C-SRAM configurations using the double pumping technique achieved the highest performance to process vectorized MAC operations compared to the others configurations...
With the rise of computationally expensive application domains such as machine learning, genomics, a...
Embedded memory remains a major bottleneck in current integrated circuit design in terms of silicon ...
Graphics Processing Units (GPUs) and other throughput processing architectures have scaled performan...
International audienceThis paper presents a new methodology for automating the Computational SRAM (C...
International audienceThis article presents Computational SRAM (C-SRAM) solution combining In- and N...
International audience—In the context of highly data-centric applications, close reconciliation of c...
International audienceComputational SRAM (C-SRAM) is a new computing solution for Near-Memory Comput...
International audienceFor big data applications, bringing computation to the memory is expected to r...
In the low-end mobile processor market, power, energy, and area budgets are significantly lower than...
Digital computation has penetrated diversity of applications such as audio visual communication, bio...
Moore’s Law predicted that the number of transistors on a chip would double approximately every 2 ye...
The well-known Moore's Law is about to end after CMOS devices using 7nm process technology are widel...
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Comput...
(c) 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for...
Pervasive computing calls for ultra-low-power devices to extend the battery life enough to enable us...
With the rise of computationally expensive application domains such as machine learning, genomics, a...
Embedded memory remains a major bottleneck in current integrated circuit design in terms of silicon ...
Graphics Processing Units (GPUs) and other throughput processing architectures have scaled performan...
International audienceThis paper presents a new methodology for automating the Computational SRAM (C...
International audienceThis article presents Computational SRAM (C-SRAM) solution combining In- and N...
International audience—In the context of highly data-centric applications, close reconciliation of c...
International audienceComputational SRAM (C-SRAM) is a new computing solution for Near-Memory Comput...
International audienceFor big data applications, bringing computation to the memory is expected to r...
In the low-end mobile processor market, power, energy, and area budgets are significantly lower than...
Digital computation has penetrated diversity of applications such as audio visual communication, bio...
Moore’s Law predicted that the number of transistors on a chip would double approximately every 2 ye...
The well-known Moore's Law is about to end after CMOS devices using 7nm process technology are widel...
Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Comput...
(c) 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for...
Pervasive computing calls for ultra-low-power devices to extend the battery life enough to enable us...
With the rise of computationally expensive application domains such as machine learning, genomics, a...
Embedded memory remains a major bottleneck in current integrated circuit design in terms of silicon ...
Graphics Processing Units (GPUs) and other throughput processing architectures have scaled performan...