Microsoft Technology Licensing, LLC

Apple Inc.

Empire Technology Development LLC

Onur Mutlu

Thomas Moscibroda

Jose Alberto Joao

William Henry Mangione-Smith

Stephan G Meier

Tyler J Huberty

Jeremie S Kim

Minesh H Patel

Thomas Moscibrod

Techniques are disclosed for obtaining data using memory timing characteristics. In some embodiments, a physical unclonable function is used to obtain the data. In various embodiments, a computer system programs a timing parameter of a memory accessible by the computer system to a value that is outside of a specified operable range for the timing parameter. In various embodiments, the computer system performs one or more memory operations to a least a portion of the memory and detects a pattern of errors in the portion of the memory. In some embodiments, the computer system generates a response dependent on the pattern of errors. The response may be used to identify the computer system.

Security techniques based on memory timing characteristics

Parallelism-aware scheduling of memory requests of threads in shared memory controllers. Parallel scheduling is achieved by prioritizing threads that already have requests being serviced in the memory banks. A first algorithm prioritizes requests of the last-scheduled thread that is currently being serviced. This is accomplished by tracking the thread that generated the last-scheduled request (if the request is still being serviced), and then scheduling another request from the same thread if there is an outstanding ready request from the same thread. A second algorithm prioritizes the requests of all threads that are currently being serviced. This is accomplished by tracking threads that have at least one request currently being serviced in the banks, and assigning the highest priority to these threads in the scheduling decisions. If there are no outstanding requests from any thread having requests that are being serviced, the algorithm defaults back to a baseline scheduling algorithm.

Parallelism-aware memory request scheduling in shared memory controllers

As microprocessors incorporate more and more devices on a single chip, dedicated buses have given way to on-chip interconnection networks ('OCIN'). Routers in a bufferless OCIN as described herein rank and prioritize flits. Flits traverse a productive path towards their destination or undergo temporary deflection to other non-productive paths, without buffering. Eliminating the buffers of on-chip routers reduces power consumption and heat dissipation while freeing up chip surface area for other uses. Furthermore, bufferless design enables purely local flow control of data between devices in the on-chip network, reducing router complexity and enabling reductions in router latency. Router latency reductions are possible in the bufferless on-chip routing by using lookahead links to send data between on-chip routers contemporaneously with flit traversals.

Bufferless routing in on-chip interconnection networks

Techniques for reliable communication in an on-chip network of a multi-core processor are provided. Packets are tagged with tags that define reliability requirements for the packets. The packets are routed in accordance with the reliability requirements. The reliability requirements and routing using them can ensure reliable communication in the on-chip network.

Reliable communications in on-chip networks

A 'request scheduler' provides techniques for batching and scheduling buffered thread requests for access to shared memory in a general-purpose computer system. Thread-fairness is provided while preventing short- and long-term thread starvation by using 'request batching.' Batching periodically groups outstanding requests from a memory request buffer into larger units termed &#x201c;batches&#x201d; that have higher priority than all other buffered requests. Each &#x201c;batch&#x201d; may include some maximum number of requests for each bank of the shared memory and for some or all concurrent threads. Further, average thread stall times are reduced by using computed thread rankings in scheduling request servicing from the shared memory. In various embodiments, requests from higher ranked threads are prioritized over requests from lower ranked threads. In various embodiments, a parallelism-aware memory access scheduling policy improves intra-thread bank-level parallelism. Further, rank-based request scheduling may be performed with or without batching.

Prioritization of multiple concurrent threads for scheduling requests to shared memory

Systems and methods that coordinate operations among a plurality of memory controllers to make a decision for performing an action based in part on state information. A control component facilitates exchange of information among memory controllers, wherein exchanged state information of the memory controllers are further employed to perform computations that facilitate the decision making process.

Coordination among multiple memory controllers

Systems and methodologies for stall-time fair memory access scheduling for shared memory systems are provided herein. A stall-time fairness policy can be applied in accordance with various aspects described herein to schedule memory requests from threads sharing a memory system. To this end, a Stall-Time Fair Memory scheduler (STFM) algorithm can be utilized, wherein memory-related slowdown experienced by a group of threads due to interference from other threads is equalized. Additionally and/or alternatively, a traditional scheduling policy such as first-ready first-come-first-serve (FR-FCFS) can be utilized in combination with a cap on column-over-row reordering of memory requests, thereby reducing the amount of stall-time unfairness imposed by such traditional scheduling policies. Further, various aspects described herein can perform memory scheduling based on thread weights and/or other parameters, which can be configured in hardware and/or software.

Software-configurable and stall-time fair memory access scheduling mechanism for shared memory systems

Controlling interference in shared memory systems using parallelism-aware batch scheduling

Providing for multi-tiered RAM control is provided herein. As an example, a RAM access management system can include multiple input controllers each having a request buffer and request scheduler. Furthermore, a request buffer associated with a controller can vary in size with respect to other buffers. Additionally, request schedulers can vary in complexity and can be optimized at least for a particular request buffer size. As a further example, a first controller can have a large memory buffer and simple scheduling algorithm optimized for scalability. A second controller can have a small memory buffer and a complex scheduler, optimized for efficiency and high RAM performance. Generally, RAM management systems described herein can increase memory system scalability for multi-core parallel processing devices while providing an efficient and high bandwidth RAM interface.

Multi-level DRAM controller to manage access to DRAM

A frequency-based prediction of indirect jumps executing in a computing environment is provided. Illustratively, a computing environment comprises a prediction engine that processes data representative of indirect jumps performed by the exemplary computing environment according to a selected frequency-based prediction paradigm. Operatively, the exemplary prediction engine can keep track of targets, in a table, taken for each indirect jump and program context (e.g., branch history and/or path information) of an exemplary computing program. Further, the prediction engine can also store a frequency counter associated with each target in the exemplary table. Illustratively, the frequency counter can record the number of times a target was taken in the recent past executions of an observed one or more indirect jump. The prediction engine can supply the target address of an indirect jump based on the values of the frequency counters of each stored target address.

Target-frequency based indirect jump prediction for high-performance processors

Systems and methods are provided to detect instances where dynamic predication of indirect jumps (DIP) is considered to be ineffective utilizing data collected on the recent effectiveness of dynamic predication on recently executed indirect jump instructions. Illustratively, a computing environment comprises a DIP monitoring engine cooperating with a DIP monitoring table that aggregates and processes data representative of the effectiveness of DIP on recently executed jump instructions. Illustratively, the exemplary DIP monitoring engine collects and processes historical data on DIP instances, where, illustratively, a monitored instance can be categorized according to one or more selected classifications. A comparison can be performed for currently monitored indirect jump instructions using the collected historical data (and classifications) to determine whether DIP should be invoked by the computing environment or whether to invoke other indirect jump prediction paradigms.

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Kirkland, WA, United States of America

Onur Mutlu