Abstract: A system comprises a source block buffer and a plurality of hardware motion estimation search processing units in communication with the source block buffer. The source block buffer is configured to store at least a portion of a source block of a source frame of a video. The plurality of hardware motion estimation search processing units are configured to perform at least a portion of a motion estimation for the source block at least in part in parallel across a plurality of different reference frames of the video.

Abstract: A system includes a first integrated circuit package including a first group of one or more artificial intelligence processing units and a first chip-to-chip interconnect communication unit and a second integrated circuit package including a second group of one or more artificial intelligence processing units and a second chip-to-chip interconnect communication unit. The system also includes an interconnect between the first integrated circuit package and the second integrated circuit package, wherein the first chip-to-chip interconnect communication unit and the second chip-to-chip interconnect communication unit manage ethernet-based communication via the interconnect using a layered communication architecture supporting a credit-based data flow control and a retransmission data flow control.

Abstract: A scalable hardware accelerator configured to compute video quality metrics is disclosed. In some embodiments, an accelerator for video quality metrics comprises an application-specific integrated circuit that includes a buffer memory configured to store at least a portion of a reference frame of a video and at least a corresponding portion of a distorted frame of a transcoded version of the video and that includes a processing unit configured to receive data from the buffer memory and compute a perception-based video quality metric for the distorted frame with respect to the reference frame.

Abstract: An example disclosed system may include a hardware video encoding pipeline (HVEP), the HVEP that includes a prediction module that generates, using a primary prediction mode, a primary encode of a portion of a video stream, and using a secondary prediction mode, a secondary encode of the portion of the video stream. The HVEP may also include (1) a rate-distortion optimization (RDO) module that determines a primary cost associated with the primary encode and a secondary cost associated with the secondary encode, (2) a quality metric (QM) module that determines a primary QM associated with the primary encode and a secondary QM associated with the secondary encode, and (3) a decision module that selects, for an encoding of the video stream, at least one of the primary prediction mode and the secondary prediction mode based on the primary cost, the secondary cost, the primary QM, and the secondary QM.

Abstract: A disclosed system may include a hardware distortion data pipeline that may include (1) a quantization module that generates a quantized data set, (2) an inverse quantization module that generates, from the quantized data set, an inverse quantized data set by executing an inverse quantization of the quantized data set, and (3) an inverse transformation module that generates an inversely transformed data set by executing an inverse transformation of the inverse quantized data set. The system may also include a hardware determination pipeline that determines a distortion metric based on the inversely transformed data set and the residual frame data set, and a hardware token rate pipeline that determines, based on the quantized data set, a token rate for an encoding of the residual frame data set via a video encoding pipeline. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: An example system may include a primary mode decision module, included in a hardware video encoding pipeline, that (1) receives video data for encoding in accordance with a video encoding standard, and (2) identifies, from an initial set of prediction modes supported by the video encoding standard, a primary set of prediction modes for encoding the video data in accordance with the video encoding standard. The example system may also include a secondary mode decision module that (1) determines, for each prediction mode included in the primary set of prediction modes and based on the video data, a cost associated with the prediction mode, and (2) selects, from the primary set of prediction modes and based on the determined costs associated with the prediction modes included in the primary set of prediction modes, a prediction mode for encoding of the video data by the hardware video encoding pipeline.

Abstract: Techniques for detecting skipped prediction units in an encoder are disclosed. Control information associated with a prediction unit of a video frame is received at a node of a video encoding pipeline used to compress the video frame. A skip decision for the prediction unit is made by analyzing transform units comprising the prediction unit. The skip decision indicates whether or not the prediction unit comprises a skipped prediction unit during encoding. The skip decision for the prediction unit is provided to a downstream node of the video encoding pipeline.

Abstract: A count circuit for symbol statistics is disclosed that is configured to read from an address of a buffer memory a count value stored at the address in response to receiving a first of a plurality of input values comprising the address, serially increment the count value for each of the received plurality of input values comprising the address, and write an incremented count value at the address of the buffer memory after a last of the plurality of input values comprising the address has been counted. Reading from the buffer memory is disabled for all but the first of the plurality of input values comprising the address. Writing to the buffer memory is disabled for all but the last of the plurality of input values comprising the address.

Abstract: A disclosed computer-implemented method may include (1) selecting, from a video stream, a reference frame and a current frame, (2) collecting a reference histogram of the reference frame and a current histogram of the current frame, and (3) generating a smoothed reference histogram by applying a smoothing function to at least a portion of the reference histogram. In some examples, the computer-implemented method may also include (1) determining a similarity metric between the smoothed reference histogram and the current histogram and, (2) when the similarity metric is greater than a threshold value, applying weighted prediction during a motion estimation portion of an encoding of the video stream. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: A system that includes a pixel processing stage decoupled from an entropy coding stage is disclosed. The pixel processing results comprise quantized transform coefficients that are divided into component blocks. The component blocks including non-zero data are identified. An optimized version of the pixel processing results for storage in a buffer storage is generated. The optimized version includes an identification of which of the component blocks include non-zero data, and the optimized version includes contents of one or more of the component blocks that include non-zero data, without including contents of one or more of the component blocks that only include zero data. The optimized version of the pixel processing results is provided for storage in the buffer storage. The optimized version of the pixel processing results from the buffer storage is received and processed to generate an unpacked version of the pixel processing results for use in entropy coding.

Abstract: An example system may include a primary mode decision module, included in a hardware video encoding pipeline, that (1) receives video data for encoding in accordance with a video encoding standard, and (2) identifies, from an initial set of prediction modes supported by the video encoding standard, a primary set of prediction modes for encoding the video data in accordance with the video encoding standard. The example system may also include a secondary mode decision module that (1) determines, for each prediction mode included in the primary set of prediction modes and based on the video data, a cost associated with the prediction mode, and (2) selects, from the primary set of prediction modes and based on the determined costs associated with the prediction modes included in the primary set of prediction modes, a prediction mode for encoding of the video data by the hardware video encoding pipeline.

Abstract: A disclosed system may include a hardware distortion data pipeline that may include (1) a quantization module that generates a quantized data set, (2) an inverse quantization module that generates, from the quantized data set, an inverse quantized data set by executing an inverse quantization of the quantized data set, and (3) an inverse transformation module that generates an inversely transformed data set by executing an inverse transformation of the inverse quantized data set. The system may also include a hardware determination pipeline that determines a distortion metric based on the inversely transformed data set and the residual frame data set, and a hardware token rate pipeline that determines, based on the quantized data set, a token rate for an encoding of the residual frame data set via a video encoding pipeline. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: A disclosed method may include storing, within a hardware memory device included as part of a rate—distortion optimization (RDO) hardware pipeline, at least one transform unit table that (1) is pregenerated from a seed probability table for transformation of video data in accordance with a video encoding standard, (2) corresponds to a transform operation supported by the video encoding standard, and (3) corresponds to a transform unit included in the RDO hardware pipeline. The method may also include determining, by accessing the transform unit table, an RDO token rate for an encoding of the video data by a hardware video encoding pipeline that includes the RDO hardware pipeline, and selecting, based on the RDO token rate, a transform operation for the encoding of the video data.

Abstract: A mode decision component is configured to determine the costs of different modes for a selected partition of a frame of a video using an estimated compression coding data, which is calculated prior to a corresponding actual compression coding data being calculated based on another partition immediately prior to the selected partition in a partition processing order. The estimated compression coding data is determined based on a previously calculated compression coding data calculated based on a completed partition prior to the selected partition in the partition processing order. The mode decision component is configured to use the determined costs to select one of the modes. An encoder component is configured to use the selected mode to encode the selected partition by using the corresponding actual compression coding data calculated based on the another partition immediately prior to the selected partition in the partition processing order.

Abstract: A method for sharing the motion estimation and mode decision results and decisions of one codec with another codec is disclosed. A video is received to be transcoded into a plurality of different output encodings of a plurality of different codecs. Each codec has a different video encoding format. A shared motion estimation and a shared mode decision processing of the video are performed. One or more results of the shared mode decision processing shared across the plurality of different codecs are used to encode the video into the plurality of different output encodings of the plurality of different codecs.

Abstract: A system comprises a memory storage configured to store at least a portion of a frame of a video and a hardware motion estimation search processing unit configured to perform at least a portion of a motion estimation search for the video for a plurality of different block sizes. The hardware motion estimation search processing unit is configured to perform the motion estimation search using a plurality of source sub-blocks of a first block size to determine a first type of comparison evaluation values for the first block size. A combination of values included in the first type of comparison evaluation values is utilized to determine at least one second type of comparison evaluation values for a second block size, wherein the second block size is larger than the first block size.

Abstract: A quantized transform coefficient matrix is partitioned into a sequence of partition portions. The coefficients of the matrix are grouped into the sequence of partition portions based on a hardware implemented scan order. Each partition portion is processed in an order of the sequence in a first pass. For each partition portion, a group of coefficients in the partition portion is determined. For each partition portion, a first data rate estimation for the quantized transform coefficient matrix is updated based on at least some coefficients of the group of coefficients in the partition portion and a maximum end-of-block. For each partition portion, an end-of-block estimation of the quantized transform coefficient matrix is updated based on at least some coefficients of the group of coefficients in the partition portion. A first resulting data rate estimation and a true end-of-block of the quantized transform coefficient matrix are determined after the first pass.

Abstract: A disclosed computer-implemented method may include (1) selecting, from a video stream, a reference frame and a current frame, (2) collecting a reference histogram of the reference frame and a current histogram of the current frame, and (3) generating a smoothed reference histogram by applying a smoothing function to at least a portion of the reference histogram. In some examples, the computer-implemented method may also include (1) determining a similarity metric between the smoothed reference histogram and the current histogram and, (2) when the similarity metric is greater than a threshold value, applying weighted prediction during a motion estimation portion of an encoding of the video stream. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: A system for facilitating efficient hardware-firmware interactions may include (i) a plurality of memory registers, (ii) a hardware module that directly reads from and writes to the plurality of memory registers and is configured to interpret a special marker that distinguishes between register write operations and non-register-write operations, and (iii) a firmware module that directs the hardware module to perform operations at least in part by sending the special marker. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: The disclosed computer-implemented method may include receiving video data to be encoded, determining pixels for a first transform unit (TU) of a first prediction unit (PU) of a square shape of the video data, storing the pixels in a buffer, performing intra-prediction for a second PU by reusing the stored pixels for a second TU of the second PU, and encoding the video data based on the intra-prediction. A system may include a video encoder and/or a tape holder apparatus. The tape holder apparatus may include a cubical tape holder to hold multiple tape cartridges in a stack, wherein a tape cartridge may be inserted into a top of the cubical tape holder. The tape holder apparatus may include a handle and a horizontal slot enabling a single tape cartridge to be pushed out from a bottom of the stack. Various other methods, systems, and apparatuses are also disclosed.