Patents Assigned to Blaize, Inc.
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Publication number: 20240428411Abstract: Systems and methods are disclosed for predicting one or more medical conditions utilizing digital images and employing artificial intelligent algorithms. The system offers accurate predictions utilizing quantized pre-trained deep learning model. The pre-trained deep learning model is trained on data samples and later refined as the system processes more digital images or new medical conditions are incorporated. One pre-trained deep learning model is used to predict the probability of one or more medical conditions and identify locations in the digital image effected by the one or more medical conditions. Further, one pre-trained deep learning model utilizing additional data and plurality of digital images, forecasts rate of infection and spread of the medical condition over time.Type: ApplicationFiled: September 10, 2024Publication date: December 26, 2024Applicant: Blaize, Inc.Inventors: Deepak Chandra Bijalwan, Dinakar C. Munagala
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Publication number: 20240411587Abstract: Disclosed herein is a graph streaming processing system comprising a thread scheduler comprising a first component and a second component. The first component is configured to schedule a first set of threads of a first node to a first processor associated with the first node and initialize status of a completion pointer to an initial value. The completion pointer is associated with a command buffer of the first node. The first component is configured to detect the execution of the first set of threads and generation of a data unit and update the status of the completion pointer to an updated value indicating execution of the first set of threads in response to the generation of the data unit. The second component is configured to schedule a second set of threads of a plurality of second nodes to a second processor based on the status of the completion pointer.Type: ApplicationFiled: July 1, 2023Publication date: December 12, 2024Applicant: Blaize, Inc.Inventors: Venkata Ganapathi Puppala, Kota Vamsi Darsi, Matthew Fortune
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Publication number: 20240411560Abstract: Methods, systems. and apparatuses for graph streaming processing are disclosed. One method includes receiving, by a thread scheduler, a group of threads, calculating a resource requirement for execution of the group of threads, calculating resource availability in a plurality of processors of each of a plurality of processor arrays, dispatching the group of threads to a selected one of plurality of processors of processor arrays, scheduling a group load instruction for all threads of the group of threads, including loading into a group load register a subset of inputs of the input tensor for processing of each thread of the group of threads, wherein the group load register provides the subset of the inputs of the input tensor to the group of threads of the selected one of the plurality of processors, wherein all threads of the group of threads are synchronized when executing the group load instruction.Type: ApplicationFiled: June 12, 2023Publication date: December 12, 2024Applicant: Blaize Inc.Inventors: Kota Vamsi Krishna Darsi, Sarvendra Govindammagari, Venkata Divyabharathi Palaparthy, Venkata Ganapathi Puppala, Satyaki Koneru
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Publication number: 20240404262Abstract: The present disclosure relates to a system and method of performing quantization of a neural network having multiple layers. The method comprises receiving a floating-point dataset as input dataset and determining a first shift constant for first layer of the neural network based on the input dataset. The method also comprises performing quantization for the first layer using the determined shift constant of the first layer. The method further comprises determining a next shift constant for next layer of the neural network based on output of a layer previous to the next layer, and performing quantization for the next layer using the determined next shift constant. The method further comprises iterating the steps of determining shift constant and performing quantization for all layers of the neural network to generate fixed point dataset as output.Type: ApplicationFiled: August 13, 2024Publication date: December 5, 2024Applicant: Blaize, Inc.Inventors: Deepak Chandra Bijalwan, Pratyusha Musunuru
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Patent number: 12141606Abstract: Methods, systems, and apparatuses for graph stream processing are disclosed. One apparatus includes a cascade of graph streaming processors, wherein each of the graph streaming processor includes a processor array, and a graph streaming processor scheduler. The cascade of graph streaming processors further includes a plurality of shared command buffers, wherein each shared command buffer includes a buffer address, a write pointer, and a read pointer, wherein for each of the plurality of shared command buffers a graph streaming processor writes commands to the shared command buffer as indicated by the write pointer of the shared command buffer and the graph streaming processor reads commands from the shared command buffer as indicated by the read pointer, wherein at least one graph streaming processor scheduler operates to manage the write pointer and the read pointer to avoid overwriting unused commands of the shared command buffer.Type: GrantFiled: October 16, 2023Date of Patent: November 12, 2024Assignee: Blaize, Inc.Inventors: Venkata Ganapathi Puppala, Sarvendra Govindammagari, Lokesh Agarwal, Satyaki Koneru
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Publication number: 20240364104Abstract: Methods, systems, and apparatuses for adaptive power supply voltage transient protection are disclosed. One system includes a power supply, a voltage transient sensor, and a power control processing entity. The power supply operates to provide power to one or more processors. The voltage transient sensor is connected to the power supply and operates to sense voltage transients on the power supply at greater than a predetermined speed or rate. The power control processing entity operates to receive a representation of the sensed voltage transients and adjust a power load based on the sensed voltage transients.Type: ApplicationFiled: July 7, 2024Publication date: October 31, 2024Applicant: Blaize, Inc.Inventor: Sebastian Artur Ciesluk
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Patent number: 12112478Abstract: Systems and methods are disclosed for predicting one or more medical conditions utilizing digital images and employing artificial intelligent algorithms. The system offers accurate predictions utilizing quantized pre-trained deep learning model. The pre-trained deep learning model is trained on data samples and later refined as the system processes more digital images or new medical conditions are incorporated. One pre-trained deep learning model is used to predict the probability of one or more medical conditions and identify locations in the digital image effected by the one or more medical conditions. Further, one pre-trained deep learning model utilizing additional data and plurality of digital images, forecasts rate of infection and spread of the medical condition over time.Type: GrantFiled: December 19, 2023Date of Patent: October 8, 2024Assignee: Blaize, Inc.Inventors: Deepak Chandra Bijalwan, Dinakar C. Munagala
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Patent number: 12100196Abstract: The present disclosure relates to a system and method of performing quantization of a neural network having multiple layers. The method comprises receiving a floating-point dataset as input dataset and determining a first shift constant for first layer of the neural network based on the input dataset. The method also comprises performing quantization for the first layer using the determined shift constant of the first layer. The method further comprises determining a next shift constant for next layer of the neural network based on output of a layer previous to the next layer, and performing quantization for the next layer using the determined next shift constant. The method further comprises iterating the steps of determining shift constant and performing quantization for all layers of the neural network to generate fixed point dataset as output.Type: GrantFiled: March 21, 2022Date of Patent: September 24, 2024Assignee: Blaize, Inc.Inventors: Deepak Chandra Bijalwan, Pratyusha Musunuru
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Patent number: 12057697Abstract: Methods, systems, and apparatuses for adaptive power supply voltage transient protection are disclosed. One system includes a system on a chip (SOC), wherein the SOC includes a power supply, a voltage transient sensor, and a power control processing entity. The power supply operates to provide power to one or more processors operating on the SOC. The voltage transient sensor is connected to the power supply and operates to sense voltage transients on the power supply at greater than a predetermined speed or rate. The power control processing entity operates to receive a digital representation of the sensed voltage transients and adjust a power load of the SOC based on the sensed voltage transients.Type: GrantFiled: December 7, 2021Date of Patent: August 6, 2024Assignee: Blaize, Inc.Inventor: Sebastian Artur Ciesluk
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Publication number: 20240221381Abstract: Methods, systems and apparatuses for a custom artificial neural network (ANN) architecture are disclosed.Type: ApplicationFiled: January 11, 2024Publication date: July 4, 2024Applicant: Blaize, Inc.Inventors: Ilya A. Balabin, Adam P. Geringer, Dmitry Zakharchenko
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Publication number: 20240119596Abstract: Systems and methods are disclosed for predicting one or more medical conditions utilizing digital images and employing artificial intelligent algorithms. The system offers accurate predictions utilizing quantized pre-trained deep learning model. The pre-trained deep learning model is trained on data samples and later refined as the system processes more digital images or new medical conditions are incorporated. One pre-trained deep learning model is used to predict the probability of one or more medical conditions and identify locations in the digital image effected by the one or more medical conditions. Further, one pre-trained deep learning model utilizing additional data and plurality of digital images, forecasts rate of infection and spread of the medical condition over time.Type: ApplicationFiled: December 19, 2023Publication date: April 11, 2024Applicant: Blaize, Inc.Inventors: Deepak Chandra Bijalwan, Dinakar C. Munagala
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Patent number: 11908132Abstract: Systems and methods are disclosed for predicting one or more medical conditions utilizing digital images and employing artificial intelligent algorithms. The system offers accurate predictions utilizing quantized pre-trained deep learning model. The pre-trained deep learning model is trained on data samples and later refined as the system processes more digital images or new medical conditions are incorporated. One pre-trained deep learning model is used to predict the probability of one or more medical conditions and identify locations in the digital image effected by the one or more medical conditions. Further, one pre-trained deep learning model utilizing additional data and plurality of digital images, forecasts rate of infection and spread of the medical condition over time.Type: GrantFiled: April 23, 2021Date of Patent: February 20, 2024Assignee: Blaize, Inc.Inventors: Deepak Chandra Bijalwan, Dinakar C. Munagala
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Patent number: 11908193Abstract: Methods, systems and apparatuses for a custom artificial neural network (ANN) architecture are disclosed.Type: GrantFiled: November 13, 2020Date of Patent: February 20, 2024Assignee: Blaize, Inc.Inventors: Ilya A. Balabin, Adam P. Geringer, Dmitry Zakharchenko
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Publication number: 20240037923Abstract: Methods, systems, and apparatuses for unsupervised data drift detection for classification neural networks are disclosed.Type: ApplicationFiled: September 28, 2022Publication date: February 1, 2024Applicant: Blaize, Inc.Inventors: Adam P. Geringer, Val G. Cook
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Publication number: 20240036921Abstract: Methods, systems, and apparatuses for graph stream processing are disclosed. One apparatus includes a cascade of graph streaming processors, wherein each of the graph streaming processor includes a processor array, and a graph streaming processor scheduler. The cascade of graph streaming processors further includes a plurality of shared command buffers, wherein each shared command buffer includes a buffer address, a write pointer, and a read pointer, wherein for each of the plurality of shared command buffers a graph streaming processor writes commands to the shared command buffer as indicated by the write pointer of the shared command buffer and the graph streaming processor reads commands from the shared command buffer as indicated by the read pointer, wherein at least one graph streaming processor scheduler operates to manage the write pointer and the read pointer to avoid overwriting unused commands of the shared command buffer.Type: ApplicationFiled: October 16, 2023Publication date: February 1, 2024Applicant: Blaize, Inc.Inventors: Venkata Ganapathi Puppala, Sarvendra Govindammagari, Lokesh Agarwal, Satyaki Koneru
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Publication number: 20230418666Abstract: Disclosed herein is a graph streaming neural network processing system comprising a first processor array, a second processor, and a thread scheduler. The thread scheduler dispatches a thread of a first node to the first processor array or the second processor, wherein the thread is executed to generate output data comprising a data unit stored in a private data buffer of the second processor. The thread scheduler determines that the data unit is sufficient for executing a thread of a second node. The second node is dependent on the output data generated by execution of a plurality of threads of the first node. Upon determining that the data unit is sufficient, the thread scheduler dispatches the thread of the second node. The thread scheduler determines to dispatch a subsequent thread of the first node for execution when a predefined threshold buffer size is available on the private data buffer.Type: ApplicationFiled: June 16, 2023Publication date: December 28, 2023Applicant: Blaize Inc.Inventors: Venkata Ganapathi Puppala, Val G. Cook, Srinivasulu Nagisetty
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Patent number: 11853762Abstract: Systems, apparatuses and methods are disclosed for efficient management of registers in a graph stream processing (GSP) system. The GSP system includes a thread scheduler module operative to initiate a Single Instruction Multiple Data (SIMD) thread, the SIMD thread including a dispatch mask with an initial value. A thread arbiter module operative to select an instruction from the instructions and provide the instruction to each of one or more compute resources, and an instruction iterator module, associated with the each of one or more compute resources operative to determine a data type of the instruction. The instruction iterator module iteratively executes the instruction based on the data type and the dispatch mask.Type: GrantFiled: May 20, 2022Date of Patent: December 26, 2023Assignee: Blaize, Inc.Inventors: Kamaraj Thangam, Srinivasulu Nagisetty, Venkata Divya Bharathi Palaparthy, Aswathy Asok, Satyaki Koneru
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Patent number: 11829736Abstract: The present disclosure relates to a system and a method of optimizing register allocation by a processor. The method comprising receiving an intermediate representation (IR) code of a source code and initializing single instruction multiple data (SIMD) width for the IR code. The method comprising analyzing each basic block of the IR code to classify determine one or more instructions of the IR code as vector instructions, wherein each basic block is one of LOAD, STORE and arithmetic logical and multiply (ALM) instructions. The method comprising dynamically setting the SIMD width for each of the vector instructions.Type: GrantFiled: February 9, 2022Date of Patent: November 28, 2023Assignee: Blaize, Inc.Inventors: Pathikonda Datta Nagraj, Aravind Rajulapudi, Ravi Korsa
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Patent number: 11822960Abstract: Methods, systems, and apparatuses for graph stream processing are disclosed. One apparatus includes a cascade of graph streaming processors, wherein each of the graph streaming processor includes a processor array, and a graph streaming processor scheduler. The cascade of graph streaming processors further includes a plurality of shared command buffers, wherein each shared command buffer includes a buffer address, a write pointer, and a read pointer, wherein for each of the plurality of shared command buffers a first graph streaming processor writes commands to the shared command buffer as indicated by the write pointer of the shared command buffer and a second graph streaming processor reads commands from the shared command buffer as indicated by the read pointer, wherein at least one graph streaming processor scheduler operates to manage the write pointer and the read pointer to avoid overwriting unused commands of the shared command buffer.Type: GrantFiled: June 7, 2022Date of Patent: November 21, 2023Assignee: Blaize, Inc.Inventors: Venkata Ganapathi Puppala, Sarvendra Govindammagari, Lokesh Agarwal, Satyaki Koneru
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Patent number: 11755368Abstract: Systems and methods are disclosures for scheduling code in a multiprocessor system. Code is portioned into code blocks by a compiler. The compiler schedules execution of code blocks in nodes. The nodes are connected in a directed acyclical graph with a top node, terminal node and a plurality of intermediate nodes. Execution of the top node is initiated by the compiler. After executing at least one instance of the top node, an instruction in the code block indicates to the scheduler to initiate at least one intermediary node. The scheduler schedules a thread for execution of the intermediary node. The data for the nodes resides in a plurality of data buffers; the index to the data buffer is stored in a command buffer.Type: GrantFiled: August 8, 2021Date of Patent: September 12, 2023Assignee: Blaize , Inc.Inventors: Satyaki Koneru, Val G. Cook, Ke Yin