Tenstorrent Inc.

Tenstorrent Ai Ulc

Milos Trajkovic

Ljubisa Bajic

Ivan Hamer

Syed Gilani

Miles Robert Dooley

Stanislav Sokorac

Rakesh Shaji Lal

Davor Capalija

Alex Cejkov

Jasmina Vasiljevic

Utku Aydonat

Lejla Bajic

Ivan Matosevic

S Alexander Chin

Andrew Lewycky

Aleksandar Cejkov

Methods and systems relating to computational hardware are disclosed herein. One disclosed method for executing a multiplication computation using a computational hardware block includes storing a first operand and a second operand for the multiplication computation. The first operand includes a first set of bit strings. The second operand includes a second set of bit strings. The method also includes multiplying the first set of bit strings and the second set of bit strings in a set of temporal phases using the computational hardware block. Each temporal phase uses a different group of bit strings from the first set of bit strings and the second set of bit strings. A cardinality of the set of temporal phases is determined by a fidelity control value. The fidelity control value adaptively sets a fidelity of execution of the multiplication computation.

Multiplication hardware block with adaptive fidelity control system

Methods and systems related to the efficient execution of complex computations by a multicore processor and the movement of data among the various processing cores in the multicore processor are disclosed. A multicore processor includes a set of processing cores and associated sets of processing pipelines, core controllers, routers, and network interface units. The multicore processor also includes a computation layer, for conducting computations using the set of processing cores, with executable instructions for the set of processing pipelines which are executed by the set of core controllers. The multicore processor also includes a network-on-chip layer, for connecting the set of processing cores in the multicore processor, with executable instructions for the set of routers and the set of network interface units. The multicore processor also includes a set of programmable controllers, with executable instructions for reformatting computational data from the computation layer for transmission through the network-on-chip layer.

Overlay layer for network of processor cores

Methods and systems relating to improved processing architectures with pre-staged instructions are disclosed herein. A disclosed processor includes a memory, at least one functional processing unit, a bus, a set of instruction registers configured to be loaded, using the bus, with a set of pre-staged instructions from the memory, and a logic circuit configured to provide the set of pre-staged instructions from the set of instruction registers to the at least one functional processing unit in response to receiving an instruction from the instruction memory.

Pre-staged instruction registers for variable length instruction set machine

A processing core for the efficient execution of a directed graph is disclosed. The processing core includes a memory and a first and a second data tile stored in the memory. The first and second data tiles include a first and a second set of data elements stored contiguously in the memory. The processing core also includes metadata relationally stored with the first data tile in the memory. The processing core also includes an execution engine, a control unit, and an instruction. Execution of the instruction uses the execution engine, a first data element in the first set of data elements, and a second data element in the second set of data elements. The control unit conditions execution of the instruction using the metadata. A standard execution of the instruction generates a standard output. A conditional execution of the instruction operation generates a conditionally executed output.

Processing core with meta data actuated conditional graph execution

Methods and systems relating to improved processing architectures with pre-staged instructions are disclosed herein. A disclosed processor includes an instruction memory, at least one functional processing unit, a bus, a set of instruction registers configured to be loaded, using the bus, with a set of pre-staged instructions from the instruction memory, and a logic circuit configured to provide the set of pre-staged instructions from the set of instruction registers to the at least one functional processing unit in response to receiving an instruction from the instruction memory.

Processing cores with the ability to suppress operations based on a contribution estimate for those operations for purposes of increasing the overall performance of the core are disclosed. Associated methods that can be conducted by such processing cores are also disclosed. One such method includes generating a reference value for a composite computation. A complete execution of the composite computation generates a precise output and requires execution of a set of component computations. The method also includes generating a component computation approximation. The method also includes evaluating the component computation approximation with the reference value. The method also includes executing a partial execution of the composite computation using the component computation approximation to produce an estimated output. The method also includes suppressing the component computation, while executing the partial execution, based on the evaluation of the component computation approximation with the reference value.

Processing core with operation suppression based on contribution estimate

A processing core and associated methods for the efficient execution of a directed graph are disclosed. A disclosed processing core comprises a memory and a first data tile stored in the memory. The first data tile includes a first set of data elements and metadata stored in association with the first set of data elements. The processing core also comprises a second data tile stored in the memory. The second data tile includes a second set of data elements. The processing core also comprises an arithmetic logic unit configured to conduct an arithmetic logic operation using data from the first set of data elements and the second set of data elements. The processing core also comprises a control unit configured to evaluate the metadata and control the arithmetic logic unit to conditionally execute the arithmetic logic operation based on the evaluation of the metadata.

Processing core with metadata actuated conditional graph execution

Processing cores with the ability to suppress operations based on a contribution estimate for those operation for purposes of increasing the overall performance of the core are disclosed. Associated methods that can be conducted by such processing cores are also disclosed. One such method includes generating a reference value for a composite computation. A complete execution of the composite computation generates a precise output and requires execution of a set of component computations. The method also includes generating a component computation approximation. The method also includes evaluating the component computation approximation with the reference value. The method also includes executing a partial execution of the composite computation using the component computation approximation to produce an estimated output. The method also includes suppressing the component computation, while executing the partial execution, based on the evaluation of the component computation approximation with the reference value.

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Toronto, Canada

Milos Trajkovic