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In-memory computing (IMC) aims to solve the performance gap between CPU and memories introduced by the memory wall. However, it does not address the energy wall problem caused by data transfer over memory hierarchies. This paper proposes the data-locality management unit (DMU) to efficiently transfer data from a DRAM memory to a computational SRAM (C-SRAM) memory allowing IMC operations. The DMU is tightly coupled within the C-SRAM and allows one to align the data structure in order to perform effective in-memory computation. We propose a dedicated instruction set within the DMU to issue data transfers. The performance evaluation of a system integrating C-SRAM within the DMU compared to a reference scalar system architecture shows an increase from ×5.73 to ×11.01 in speed-up and from ×29.49 to ×46.67 in energy reduction, versus a system integrating C-SRAM without any transfer mechanism compared to a reference scalar system architecture.

This article describes a software environment called HybroGen, which helps to experiment binary code generation at run time. As computing architectures are getting more complex, the application performance is becoming data-dependent. The proposed experimental platform is helpful in programming applications that can be reconfigured at run time in order to be adapted for a new data environment. The HybroGen platform is adapted to heterogeneous architectures and can generate instructions for different targets. This platform allows to go farther than classical JIT compilation in many directions: the code generator is smaller by three orders of magnitude and faster by three orders of magnitude, compared to JIT (Just-In-Time) platforms, and allows making code transformation that is impossible in traditional compilation schemes, such as code generation for non von Neumann accelerators or dynamic code transformations for transprecision. The latter is illustrated in a code example: the square root with Newton’s algorithm. We also illustrate the proposed HybroGen platform with two other examples: a multiplication with a specialization on a value determined at run time, and a conversion of degrees Celsius to degrees Fahrenheit. This article presents a proof of concept of the proposed HybroGen platform in terms of its functionalities, and demonstrates the working status.