Abstract: An architecture for content-aware compression and/or encryption of various segments of a application is disclosed. The architecture advantageously allows decompression and decryption units to be placed various levels of a memory hierarchy.

Abstract: An embedded systems architecture is disclosed which can flexibly handle compression of both instruction code and data.

Abstract: A method for code compression of a program, the method comprising separating code from data. Software transformations necessary to make address mappings between compressed and uncompressed space are introduced into the code. Statistics are obtained about frequency of occurrence instructions, wherein said statistics include frequency of occurrence of two consecutive instructions. The program is parsed to identify occurrence of instructions or instruction pairs. The identified instructions are replaced with an address to a compressed bus-word table. An address mapping is generated from uncompressed address to compressed addresses.

Abstract: A dynamic memory compression architecture is disclosed which allows applications with working data sets exceeding the physical memory of an embedded system to still execute correctly. The dynamic memory compression architecture provides “on-the-fly” compression and decompression of the working data in a manner which is transparent to the user and which does not require special-purpose hardware. A new compression technique is also herein disclosed which is particularly advantageous when utilized with the above-mentioned dynamic memory compression architecture.

Abstract: A storage management architecture is disclosed which is particularly advantageous for devices such as embedded systems. The architecture provides a framework for a compression/decompression system which advantageously is software-based and which facilitates the compression of both instruction code and writeable data.

Abstract: An embedded systems architecture is disclosed which can flexibly handle compression of both instruction code and data.

Abstract: A new compression and decompression architecture is herein disclosed which advantageously uses a plurality of parallel content addressable memories of different sizes to perform fast matching during compression.

Abstract: An architecture for content-aware compression and/or encryption of various segments of a application is disclosed. The architecture advantageously allows decompression and decryption units to be placed various levels of a memory hierarchy.

Abstract: A system architecture is disclosed that can support fast random access to encrypted memory.

Abstract: Code compression is known as an effective technique to reduce instruction memory size on an embedded system. However, code compression can also be very effective in increasing the processor-to-memory bandwidth and hence provide increased system performance. A code decompression engine having plurality of dictionary tables, coupled with decoding circuitry and appropriate control circuitry, is coupled between the processor core and the instruction cache. The code decompression engine provides one-cycle decompression of compressed instructions that are intermixed with uncompressed instructions, thereby increasing processor-to-memory bandwidth and avoiding processor stalls.

Abstract: A method for code compression of a program, the method comprising separating code from data. Software transformations necessary to make address mappings between compressed and uncompressed space are introduced into the code. Statistics are obtained about frequency of occurrence instructions, wherein said statistics include frequency of occurrence of two consecutive instructions. The program is parsed to identify occurrence of instructions or instruction pairs. The identified instructions are replaced with an address to a compressed bus-word table. An address mapping is generated from uncompressed address to compressed addresses.

Abstract: The power consumption of interconnects starts to have a significant impact on a system's total power consumption. Besides increasing buses (length, width) etc. this is mostly due to deep sub-micron effects where coupling capacitances between bus lines (wire-to-wire) are in the same order of magnitude as the base capacitances (wire-to-metal-layer). At that point, encoding schemes that solely address the minimization of transitions for the purpose of power reduction do not effectively work any more. Using a physical bus model that accurately models coupling capacitances, a signal bus encoding/decoding apparatus with encoding schemes that are partially adaptive and that take coupling effects into consideration is presented. The encoding schemes do not assume any a priori knowledge that is particular to a specific application.

Abstract: A code compression method and apparatus for system-level power optimization that lessens the requirements imposed on main memory size. The apparatus utilizes a post-cache architecture that has a decompression engine that decompresses compressed object code instructions using dictionary look-up tables, branching instruction controllers and mathematical derivations based on bit toggling. The decompression engine extracts the compressed instructions from memory or the instruction/data cache using a bus compression technique to save power as the compressed instructions/data traverses the bus.

Abstract: A code compression method for system-level power optimization that lessens the requirements imposed on main memory size. The method reduces the power consumption of a complete system comprising a CPU, instruction cache, data cache, main memory, data buses and address bus. The method includes extracting compressible instruction and data portions from executable code, creating a mathematical model of the extracted code portions, class the individual instructions in the extracted portions based upon their operation codes and compressing the instructions. The compressed instructions are further compressed when extracted from memory by using bus compaction. The method is also embodied in a computer system with a processor and a memory adapted to perform the steps of the method to compress the extracted instruction portions. Additionally, the method is embodied on a computer program product bearing software instructions adapted to perform the steps of the method to compress the extracted instruction portions.

Abstract: A code compression method for system-level power optimization that lessens the requirements imposed on main memory size. The method reduces the power consumption of a complete system comprising a CPU, instruction cache, data cache, main memory, data buses and address bus. The method includes extracting compressible instruction and data portions from executable code, creating a mathematical model of the extracted code portions, class the individual instructions in the extracted portions based upon their operation codes and compressing the instructions. The compressed instructions are further compressed when extracted from memory by using bus compaction. The method is also embodied in a computer system with a processor and a memory adapted to perform the steps of the method to compress the extracted instruction portions. Additionally, the method is embodied on a computer program product bearing software instructions adapted to perform the steps of the method to compress the extracted instruction portions.

Abstract: The power consumption of interconnects starts to have a significant impact on a system's total power consumption. Besides increasing buses (length, width) etc. this is mostly due to deep sub-micron effects where coupling capacitances between bus lines (wire-to-wire) are in the same order of magnitude as the base capacitances (wire-to-metal-layer). At that point, encoding schemes that solely address the minimization of transitions for the purpose of power reduction do not effectively work any more. Using a physical bus model that accurately models coupling capacitances, a signal bus encoding/decoding apparatus with encoding schemes that are partially adaptive and that take coupling effects into consideration is presented. The encoding schemes do not assume any a priori knowledge that is particular to a specific application.

Abstract: Code compression is known as an effective technique to reduce instruction memory size on an embedded system. However, code compression can also be very effective in increasing the processor-to-memory bandwidth and hence provide increased system performance. A code decompression engine having plurality of dictionary tables, coupled with decoding circuitry and appropriate control circuitry, is coupled between the processor core and the instruction cache. The code decompression engine provides one-cycle decompression of compressed instructions that are intermixed with uncompressed instructions, thereby increasing processor-to-memory bandwidth and avoiding processor stalls.

Abstract: The power consumption of interconnects starts to have a significant impact on a system's total power consumption. Besides increasing buses (length, width) etc. this is mostly due to deep sub-micron effects where coupling capacitances between bus lines (wire-to-wire) are in the same order of magnitude as the base capacitances (wire-to-metal-layer). At that point, encoding schemes that solely address the minimization of transitions for the purpose of power reduction do not effectively work any more. Using a physical bus model that accurately models coupling capacitances, a signal bus encoding/decoding apparatus with encoding schemes that are partially adaptive and that take coupling effects into consideration is presented. The encoding schemes do not assume any a priori knowledge that is particular to a specific application.

Abstract: The power consumption of interconnects starts to have a significant impact on a system's total power consumption. Besides increasing buses (length, width) etc. this is mostly due to deep sub-micron effects where coupling capacitances between bus lines (wire-to-wire) are in the same order of magnitude as the base capacitances (wire-to-metal-layer). At that point, encoding schemes that solely address the minimization of transitions for the purpose of power reduction do not effectively work any more. Using a physical bus model that accurately models coupling capacitances, a signal bus encoding/decoding apparatus with encoding schemes that are partially adaptive and that take coupling effects into consideration is presented. The encoding schemes do not assume any a priori knowledge that is particular to a specific application.