International Business Machines Corporation

Baffle, Inc.

The University of Texas System

Calvin Lin

Ibrahim Hur

Priyadarshan Kolte

Ashmeet Sidana

Akanksha Jain

The present invention provides methods for executing a private computer program on untrusted computers. The present invention also provides for products produced by the methods of the present invention and for apparatuses used to perform the methods of the present invention.

Systems and processes for executing private programs on untrusted computers

A method, system and computer program product for cache replacement. The present invention leverages Belady's optimal replacement algorithm by applying it to past cache accesses to inform future cache replacement decisions. The occupied cache capacity of a cache is tracked at every time interval using an occupancy vector. The cache capacity is retroactively assigned to the cache lines of the cache in order of their reuse, where a cache line is considered to a cache hit if the cache capacity is available at all times between two subsequent accesses. The occupancy vector is updated using a last touch timestamp of a current memory address. A determination is made as to whether the current memory address results in a cache hit or a cache miss based on the updated occupancy vector. The replacement state for the cache line is stored using the results of the determination.

Evicting appropriate cache line using a replacement policy utilizing belady's optimal algorithm

A method for preforming memory prefetching is disclosed. A stream length histogram (SLH) is initially generated based on a stream of Read and Write requests intended for a system memory. A determination is then made whether or not to issue a prefetch command after a Read request based on information within the generated SLH. In a determination that a prefetch command should be issued, prefetch command to be sent to the system memory is issued along with other commands.

Probabilistic method for performing memory prefetching

A method for preforming memory prefetching and scheduling prefetch commands inside the memory controller is disclosed. A set of prefetch commands is generated based on a stream of Read requests intended for a system memory, and the prefetch commands are stored in a low priority queue (LPQ). A set of regular commands is generated based on a stream of Read and Write requests intended for the system memory, and the regular commands are stored in a centralized arbiter queue. One of the prefetch commands is issued from the LPQ depending on the status of the other queues in the memory controller.

Priority-based memory prefetcher

A memory controller uses a power- and performance-aware scheduler which reorders memory commands based on power priorities. Selected memory ranks of the memory device are then powered down based on rank localities of the reordered commands. The highest power priority may be given to memory commands having the same rank as the last command sent to the memory device. Any memory commands having the same power priority can be further sorted based on one or more performance criteria such as an expected latency of the memory commands and an expected ratio of read and write memory commands. To optimize the power-down function, the power-down command is only sent when the selected memory rank is currently idle, the selected memory rank is not already powered down, none of the reordered memory commands correspond to the selected rank, and a currently pending memory command cannot be issued in the current clock cycle.

DRAM power management in a memory controller

A memory controller uses a throttling mechanism which estimates a throttling delay for achieving a target power consumption, and periodically blocks all memory commands for a number of clock cycles corresponding to the throttling delay. Idle memory ranks of the memory device are powered down while the memory commands are blocked. A regression model bases the throttling delay on a plurality of operating factors and a plurality of regression coefficients for the operating factors. In the illustrative implementation the operating factors include power consumption, a current number of bank conflicts, a current number of read commands, and a current number of write commands. Different sets of regression coefficients can be programmably stored for use with different system configurations.

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Austin, TX, United States of America

Calvin Lin