Abstract: A multi-tile CASCADE fabric for large-scale neural-network inference is disclosed. Multiple CASCADE tiles, each implementing a column-oriented compute array, perform local accumulation of partial sums within columns and output only completed column sums. The tiles communicate through an inter-tile network that transfers completed results rather than intermediate partial sums, greatly reducing bandwidth and enabling near-linear scaling of throughput. Activation values are broadcast synchronously to all tiles, and a hierarchical aggregation structure combines completed column sums into final layer outputs. The architecture maintains the CASCADE principle of column-confined accumulation across tiles, chips, and racks while minimizing power and communication overhead.

Abstract: A per-column bias-initialization architecture for synchronous column-oriented neural-network compute arrays is disclosed. Before the start of a matrix-multiplication operation, each column's Hierarchical Integrated Latch Tree (HILT) loads a bias value and presents it as the initial operand of a recirculating adder that forms the column's output sum. All columns operate synchronously under a common array clock and advance row-synchronously through activations. This bias-initialization method eliminates the need for global post-processing bias addition, allowing each column's output-sum path to add its bias value without incurring extra latency, thereby improving utilization and preserving CASCADE's deterministic timing and column isolation.

Abstract: A two-bit exponent combiner circuit for FP4 (E2M1) processing elements adds two operand exponents and a normalization-carry signal from a mantissa network to produce a combined exponent output in a single clock cycle. The carry-in replaces traditional alignment and normalization hardware, allowing a minimal ripple-carry adder to complete exponent combination at multi-gigahertz frequency. Overflow and underflow are handled by simple saturation logic, eliminating barrel shifters and scaling circuitry in low-precision fused multiply-add operations.

Abstract: A column-oriented compute array executes matrix multiplication by broadcasting, for each compute row, a corresponding activation value substantially simultaneously to all columns within a clock cycle. Each column multiplies the broadcast activation by locally stored weights and accumulates partial sums within that column without any inter-column transfer of partial sums. Bias values are pre-loaded before the start of the operation and applied as initial recirculating values to per-column output-sum recirculating adders. The activation broadcast fabric is implemented as a Hierarchical Integrated Latch Tree that stages and fans out activation values in alignment with a row-synchronous compute wave, enabling high clock frequency while minimizing capacitive loading and skew. Accumulation employs truncated normalization with saturating exponent handling, with an accumulator width wider than the four-bit inputs.

Abstract: A targeted jet-cooling system removes heat from high-density compute assemblies using multiple coolant jets directed at individual heat sources. Each jet is independently tuned in flow rate, pressure, or angle to equalize flow rate and maximize thermal performance. The coolant may be a dielectric two-phase liquid at atmospheric pressure (JETSTREAM) or supercritical CO2 in a closed-loop high-pressure configuration (JETSCI). Jet arrays impinge on exposed surfaces of compute stacks mounted on a wafer- or panel-scale substrate, achieving thermal transport exceeding 100 KW per rack while sustaining computing throughput from 10 exaFLOPS to 1 zettaFLOPS per rack.

Abstract: A processing element includes a mixed precision fused multiply add datapath configured to receive an FP4 weight operand and an FP8 activation operand in a two stage pipeline. A first stage generates a mixed precision product and a second stage accumulates the product. Control circuitry adjusts local device bias within the processing element based on detected switching activity to maintain propagation delay within a predetermined range. A computing device may include an array of such processing elements, each operating with independent bias adaptation. A method of operation includes generating a mixed precision product, detecting switching activity, adjusting local device bias, and accumulating the product while maintaining controlled timing.

Abstract: A bounded-carry partial-sum adder for FP8 accumulation in a pipelined mixed-precision processing element is disclosed. The adder limits carry propagation to a predetermined depth, ensuring deterministic fixed delay independent of operand magnitude. The accumulator forms the second stage of a two-stage fused multiply-add pipeline and supports a one-cycle initiation interval while accumulating products of FP4 weight operands and FP8 activation operands. The architecture enables uniform high-frequency timing across dense arrays of processing elements.

Abstract: A pipelined fused multiply-add processing element for mixed-precision arithmetic using FP4 weight operands and FP8 activation operands is disclosed. The element forms a product of the FP4 weight and FP8 activation and accumulates the result into an FP8 accumulator using bounded-carry logic. The datapath includes a latch-defined pipeline having a two-cycle latency while sustaining a one-cycle initiation interval, allowing one new fused multiply-add operation to be accepted each clock cycle. Weight operands follow an FP4 (E2M1) format within a shared exponent domain, permitting omission of per-element exponent alignment and rounding logic. Symmetric physical layout and deterministic timing enable multi-gigahertz operation with extremely small area, supporting dense arrays of mixed-precision arithmetic units for AI inference accelerators.

Abstract: A deterministic dual-stage pipelined mixed-precision fused multiply-add processing element is disclosed. The element receives an FP4 weight operand and an FP8 activation operand, forms a mixed-precision product, and accumulates the result in FP8 precision. A latch boundary divides the datapath into first and second pipeline stages, providing fixed two-cycle latency while sustaining a one-cycle initiation interval. Symmetric routing and balanced combinational paths remove operand-dependent timing variations. The architecture supports dense arrays of billions of processing elements for high-performance AI inference.

Abstract: An underfill technique for high-density silicon-based substrates uses through-substrate gaps as capillary channels to distribute a low-modulus material from a back side to device-interconnect regions on a front side. Semiconductor devices mounted to the front surface are underfilled by partially immersing the substrate so a liquid elastomer wicks through the gaps and into microbump regions, followed by cure. Gap arrays define boundaries around device footprints, with gap geometries adapted to signal-routing density to preserve mechanical compliance of stress-relief structures. The approach enables simultaneous, void-free filling across closely spaced devices, reduces handling, and maintains the compliance of stress-relief features compared with rigid epoxy underfills. Preferred materials include addition-cure silicone elastomers with Shore A hardness less than 30 and high electrical resistivity, and post-application cleaning prepares the opposite surface for attachment features.

Abstract: Electronic substrates that carry arrays of component positions often employ edge regions with connection patterns that differ from interior positions, complicating test access. Described is loop-back routing that, at a peripheral region, redirects signals from the edge connection pattern to a verification pad field arranged to match the interior array pattern. A probe assembly with a fixed layout thus engages both interior positions and edge regions using a single probe footprint to verify continuity across large arrays. The routing may pass from an interface controller site to a through-substrate via site and then to the verification pad field, and multiple paths can be daisy-chained for concurrent checks. The approach supports high probe counts and wafer-scale substrates while reducing probe card variants and test time.

Abstract: A manufacturing process for silicon circuit boards and wafer-scale silicon circuit boards maintains the silicon substrate at substantially its original wafer thickness throughout fabrication. Through-silicon vias are etched and filled, redistribution layers are formed, and through-etched stress-relief structures are created by deep reactive-ion etching with in-situ endpoint detection. The wafer is temporarily bonded to a carrier, inverted for double-sided processing, and singulated by the same through-etch that forms compliant mechanical structures. Release is achieved by controlled thermal debonding followed by vacuum pickup and plasma cleaning. The process eliminates back-grinding, mechanical dicing, and warpage issues associated with thinned wafers, enabling reliable, full-thickness silicon boards suitable for large-area high-density interconnection.

Abstract: A hierarchical activation-broadcast network for column-oriented neural-network compute arrays is disclosed. Activation values corresponding to each processing row are distributed concurrently to all columns of processing elements through a hierarchical latch tree that fans out the signals synchronized within one clock period. The broadcast network maintains precise timing alignment among columns while minimizing capacitive loading and clock skew. The distribution fabric may be fabricated on a separate die or interposer and connected to the compute die by high-density hybrid bonds. The approach enables wide, low-skew activation delivery across large arrays, reducing energy consumption and improving frequency scalability for CASCADE architectures.

Abstract: An asynchronous and phase-interleaved column architecture for matrix multiplication in neural-network inference is disclosed. Processing elements are arranged as vertical columns that locally accumulate partial sums while activations from each processing row are broadcast concurrently to all columns. Each column operates in its own clock domain or with a controlled phase offset relative to adjacent columns, reducing simultaneous current peaks and improving signal integrity. Boundary latches and handshake circuits synchronize limited inter-domain data transfer, allowing each column to operate at a higher local frequency than global control logic. Periodic resynchronization events maintain deterministic broadcast timing. The architecture enables large compute arrays without a global high-frequency clock, reducing power noise and enabling higher effective throughput.

Abstract: A semiconductor intellectual property block for edge system-on-chip integration provides transformer-class inference under tight power and area limits. The block includes column-oriented processing arrays that accumulate partial sums within each column, a hierarchical latch distribution structure that pipelines activation broadcast, and an interface to stacked non-volatile memory supplying weights at high bandwidth. A dual-clock organization runs compute at a higher frequency than memory/control to reduce power while sustaining throughput. Fault-aware column sparing maintains full array functionality. When coupled to stacked flash providing terabyte-scale capacity, the block executes large-parameter transformer models locally with peak throughput of at least one petaFLOPS below five watts, enabling responsive edge inference without external high-bandwidth DRAM.

Abstract: Power distribution structures for high-density compute engines are disclosed. A plurality of conductive busbars are arranged in a stacked laminar array separated by dielectric films and joined to a mounting region that accepts columnar power interconnect pillars. The pillars are staked or otherwise mechanically retained in the busbar stack and are joined directly to under-bump metallization on a silicon-based interconnect substrate, thereby delivering low-voltage, high-current power without a field-removable output connector. In some implementations the stack pitch matches a column-grid array pitch of about one millimeter, ground plates are interleaved with power plates to reduce loop inductance, and selected busbars are segmented into insulated sub-busbars to define independent power domains. The assembly may be coupled to a regulator printed circuit board carrying intermediate-ratio conversion, and may operate in a dielectric liquid.

Abstract: A column-retentive activation-buffer architecture for column-oriented neural-network compute arrays is disclosed. Each column of processing elements includes a local activation buffer that stores activations received from prior broadcasts for reuse across multiple inference cycles or attention heads, thereby reducing redundant activation transfers from external memory. Lightweight synchronization signals maintain coherence between broadcast control and per-column buffers. The approach preserves CASCADE's row-wise broadcast and column-confined accumulation principles while significantly decreasing external bandwidth and power consumption.

Abstract: A compute engine for BitNet b1.58-style inference employs arrays of ultra-simple processing elements that implement ternary weights using sign selection and conditional accumulation rather than a conventional multiplier. Each processing element stores a weight encoding +1, 0, or ?1, selects a non-inverted activation, a zero, or an inverted activation accordingly, and updates a saturating accumulator while skipping accumulator clocking on zero weights. The processing elements are arranged for deterministic systolic dataflow across an all-silicon domain, enabling massive replication with low transistor count per element. Optional tiles interface via first-in first-out buffers in lieu of caches to preserve timing predictability. The approach reduces area and power while sustaining multi-gigahertz operation suited to transformer inference.

Abstract: A silicon substrate supports single-sided verification of through-silicon via (TSV) connections using verification pads on the same surface as component attachment pads. Each verification pad is independently routed to a corresponding via through redistribution-layer conductors that are electrically isolated from primary attachment paths. The configuration enables electrical continuity and isolation testing of vias without contacting the reverse side of the substrate. High-density parallel probing is achieved using a probe chip aligned to the module footprint, while coarse-pitch column grid array or power features may occupy the opposite side. Optional embodiments include loop-back routing for high-speed links, daisy-chained test groups with guard paths, and redistribution-layer bypass structures around defective regions, providing efficient and non-invasive TSV verification for passive silicon interposers and circuit boards.

Abstract: An integrated computing structure is disclosed in which a plurality of processing chips are interconnected within an all-silicon domain to present more than one billion processing elements as a unified computational resource. A silicon-implemented interconnect fabric coordinates data movement and timing across populated chip sites, and a distributed control plane maintains coherency during parallel execution. Configurations optionally employ wafer-to-wafer hybrid bonding between compute core dies and interface dies, Universal Chiplet Interconnect Express links for high-bandwidth die-to-die connections, and dynamic fault handling with in-field substitution of redundant computation columns. Methods include configuring large populations of processing elements into a coherent array, maintaining synchronous timing across the interconnect, and executing transformer-class workloads while preserving operational coherency.