DETAILED ACTION
The present application, filed on 12/28/2022 is being examined under the AIA first inventor to file provisions.
The following is a non-final First Office Action on the Merits. Claims 1-17, 21-23 are pending and have been considered below. Claims 18-20 have been cancelled in a preliminary amendment.
The following is a FINAL Office Action in response to Applicant’s amendments filed on 2/4/2026.
a. Claims 1, 4, 11, 14, 17, 22-23 are amended
b. Claims 2, 18-21 are cancelled
c. Claims 24-25 are new
Overall, claims 1, 3-17, 22-25 are examined.
Claim Rejections - 35 USC § 101
35 USC 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-17, 21-23 are rejected under 35 USC 101 because the claimed invention is not directed to patent eligible subject matter. The claimed matter is directed to a judicial exception, i.e. an abstract idea, not integrated into a practical application, and without significantly more.
Per Step 1 of the multi-step eligibility analysis, claims 1-16 are directed to a system and claims 17, 21-23 are directed to a system as well.
Thus, on its face, each independent claim and the associated dependent claims are directed to a statutory category of invention.
[INDEPENDENT CLAIMS]
Per Step 2A.1. Independent claim 1, (which is representative of independent claims 17) is rejected under 35 USC 101 because the independent claim is directed to an abstract idea, a judicial exception, without reciting additional elements that integrate the judicial exception into a practical application.
The limitations of the independent claim 1 (which is representative of independent claims 17) recite an abstract idea, shown in bold below:
[A] An integrated circuit apparatus for forward fusing a neural network, comprising:
[B] a shared random-access memory (SRAM);
[C] an external storage controller configured to access an external dynamic random- access memory (DRAM):
[D] a processing apparatus configured to
[E] load, from the DRAM, one or more feature maps into the SRAM to form an on-chip unit map,
[F] select a top unfused layer in the neural network as a starting layer of a fusion according to a fusion policy,
[G] perform the fusion in a direction of a starting point of the neural network from the starting layer to create a template fuse unit, and
[H] as the fusion proceeds to fuse layers into the template fuse unit, compute a redundancy percentage as a ratio of the amount of memory access of the on-chip unit map from the DRAM to the SRAM to the amount of normal input/output of the on-chip unit map excluding redundancy, and
[I] stop fusing additional layers into the template fuse unit when the redundancy percentage exceeds a predetermined threshold and
[J] a computing apparatus configured to
[K] perform neural network computing according to the template fuse unit on the on-chip unit map.
Independent claim 1 (which is representative of independent claims 17) recites: selecting a starting layer and performing the fusion in the direction of the starting layer ([F], [G]); computing a redundancy percentage and stopping fusing when the redundancy percentage exceeds a predetermined threshold ([H], [I]); performing the neural network computing according to the template fuse unit ([K]), which, based on the claim language and in view of the application disclosure, represents a process aimed at: “performing directional fusing (e.g., from ending point to starting point) of neural network layers”.
This is a combination that, under its broadest reasonable interpretation, covers performance of limitations expressing mathematical concepts like mathematical calculations. These fall under the Mathematical Concepts. i.e., mathematical relationships, mathematical formulas or equations, or mathematical calculations grouping of abstract ideas (see MPEP 2106.04(a)(2) I).
Accordingly, it is concluded that independent claim 1 (which is representative of independent claims 17) recites an abstract idea that corresponds to a judicial exception.
[INDEPENDENT CLAIMS – Additional Elements]
Per Step 2A.2. The identified abstract idea is not integrated into a practical application because the additional elements in the independent claims only amount to instructions to apply the judicial exception to a computer, or are a general link to a technological environment (see MPEP 2106.05(f); MPEP 2106.05(h)).
For example, the added elements “a shared random-access memory,” “an external storage controller,” “a processing apparatus” and :a computing apparatus” recite computing elements at a high level of generality, generally linking the use of a judicial exception to a particular technological environment (see MPEP 2106.05(h)), or merely using a computer as a tool to perform an abstract idea (MPEP 2106.05(f)).
These additional elements of the independent claims do not preclude from carrying out the identified abstract idea performing directional fusing (e.g., from ending point to starting point) of neural network layers, and do not serve to integrate the identified abstract idea into a practical application.
The additional steps in the independent claims, shown not bolded above, recite: load, from the DRAM, one or more feature maps into the SRAM to form an on-chip unit map ([E]). When considered individually, they amount to nothing more than receiving data, processing data, storing results or transmitting data that serves merely to implement the abstract idea using computing components for performing computer functions (corresponding to the words “apply it” or an equivalent), or merely uses a computer as a tool to perform the identified abstract idea. Thus, it is concluded that these claim elements do not integrate the identified abstract idea (performing directional fusing (e.g., from ending point to starting point) of neural network layers) into a practical application (see MPEP 2106.05(f)(2)).
Therefore, the additional claim elements of independent claim 1 (which is representative of independent claims 17) do not integrate the identified abstract idea into a practical application and the claims remain a judicial exception.
Per Step 2B. Independent claim 1 (which is representative of claims independent 17) does not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when the independent claim is reevaluated as a whole, as an ordered combination under the considerations of Step 2B, the outcome is the same like under Step 2A.2.
Overall, it is concluded that independent claims 1, 17 are deemed ineligible.
[DEPENDENT CLAIMS]
Dependent claim 3, which is representative of dependent claim 2, recites:
wherein a top layer of the template fuse unit is an input layer of the template fuse unit, the starting layer is an output layer of the template fuse unit, and
the processing apparatus
performs a pyramid fusion based on the input layer and the output layer.
When considered individually, these added claim elements further elaborate on the abstract idea identified in the independent claims, because the dependent claim continues to recite the identified abstract idea: “performing directional fusing (e.g., from ending point to starting point) of neural network layers”. The elements in this dependent claim are comparable to receiving/transmitting data, processing data, storing results or transmitting data that serves merely to implement the abstract idea using computing components for performing computer functions (corresponding to the words “apply it” or an equivalent), or merely uses a computer as a tool to perform the identified abstract idea. Thus, it is concluded that these claim elements do not integrate the identified abstract idea (“performing directional fusing (e.g., from ending point to starting point) of neural network layers”) into a practical application (see MPEP 2106.05(f)(2)).
The dependent claim elements have the same relationship to the underlying abstract idea (“performing directional fusing (e.g., from ending point to starting point) of neural network layers ”) as outlined in the independent claims analysis above. Thus, it is readily apparent that the dependent claim elements are not directed to any specific improvements of the independent claims and do not practically or significantly alter how the identified abstract idea would be performed. When considered as a whole, as an ordered combination, the dependent claim further elaborates on the previously identified abstract idea (“performing directional fusing (e.g., from ending point to starting point) of neural network layers”).
Therefore, dependent claim 3 (which is representative of dependent claim 22) is deemed ineligible.
Dependent claim 5 recites:
wherein, when performing the fusion in the direction of the starting point of the neural network, the processing apparatus
judges whether a newly added layer has already been fused, and
if the newly added layer has already been fused, the processing apparatus
stops the fusion.
When considered individually, these added claim elements further elaborate on the abstract idea identified in the independent claims, because the dependent claim continues to recite the identified abstract idea: “performing directional fusing (e.g., from ending point to starting point) of neural network layers”. The elements in this dependent claim are comparable to receiving/transmitting data, processing data, storing results or transmitting data that serves merely to implement the abstract idea using computing components for performing computer functions (corresponding to the words “apply it” or an equivalent), or merely uses a computer as a tool to perform the identified abstract idea. Thus, it is concluded that these claim elements do not integrate the identified abstract idea (“performing directional fusing (e.g., from ending point to starting point) of neural network layers”) into a practical application (see MPEP 2106.05(f)(2)).
The dependent claim elements have the same relationship to the underlying abstract idea (“performing directional fusing (e.g., from ending point to starting point) of neural network layers”) as outlined in the independent claims analysis above. Thus, it is readily apparent that the dependent claim elements are not directed to any specific improvements of the independent claims and do not practically or significantly alter how the identified abstract idea would be performed. When considered as a whole, as an ordered combination, the dependent claim further elaborates on the previously identified abstract idea (“performing directional fusing (e.g., from ending point to starting point) of neural network layers”).
Therefore, dependent claim 5 is deemed ineligible.
Dependent claim 6 recites:
wherein, when performing the fusion in the direction of the starting point of the neural network, the processing apparatus
judges whether a newly added layer has already been fused, and
if the newly added layer has already been fused, the processing apparatus
performs a fusion in a direction of an ending point of the neural network.
When considered individually, these added claim elements further elaborate on the abstract idea identified in the independent claims, because the dependent claim continues to recite the identified abstract idea: “performing directional fusing (e.g., from ending point to starting point) of neural network layers”. The elements in this dependent claim are comparable to receiving/transmitting data, processing data, storing results or transmitting data that serves merely to implement the abstract idea using computing components for performing computer functions (corresponding to the words “apply it” or an equivalent), or merely uses a computer as a tool to perform the identified abstract idea. Thus, it is concluded that these claim elements do not integrate the identified abstract idea (“performing directional fusing (e.g., from ending point to starting point) of neural network layers”) into a practical application (see MPEP 2106.05(f)(2)).
The dependent claim elements have the same relationship to the underlying abstract idea (“performing directional fusing (e.g., from ending point to starting point) of neural network layers”) as outlined in the independent claims analysis above. Thus, it is readily apparent that the dependent claim elements are not directed to any specific improvements of the independent claims and do not practically or significantly alter how the identified abstract idea would be performed. When considered as a whole, as an ordered combination, the dependent claim further elaborates on the previously identified abstract idea (“performing directional fusing (e.g., from ending point to starting point) of neural network layers”).
Therefore, dependent claim 6 is deemed ineligible.
Dependent claim 7 recites:
wherein, after the processing apparatus
performs the fusion in the direction of the starting point of the neural network,
the processing apparatus
continues to perform a fusion in a direction of an ending point of the neural network to perform a jump fusion.
When considered individually, these added claim elements further elaborate on the abstract idea identified in the independent claims, because the dependent claim continues to recite the identified abstract idea: “performing directional fusing (e.g., from ending point to starting point) of neural network layers”. The elements in this dependent claim are comparable to receiving/transmitting data, processing data, storing results or transmitting data that serves merely to implement the abstract idea using computing components for performing computer functions (corresponding to the words “apply it” or an equivalent), or merely uses a computer as a tool to perform the identified abstract idea. Thus, it is concluded that these claim elements do not integrate the identified abstract idea (“performing directional fusing (e.g., from ending point to starting point) of neural network layers”) into a practical application (see MPEP 2106.05(f)(2)).
The dependent claim elements have the same relationship to the underlying abstract idea (“performing directional fusing (e.g., from ending point to starting point) of neural network layers”) as outlined in the independent claims analysis above. Thus, it is readily apparent that the dependent claim elements are not directed to any specific improvements of the independent claims and do not practically or significantly alter how the identified abstract idea would be performed. When considered as a whole, as an ordered combination, the dependent claim further elaborates on the previously identified abstract idea (“performing directional fusing (e.g., from ending point to starting point) of neural network layers”).
Therefore, dependent claim 7 is deemed ineligible.
Dependent claim 12 recites:
wherein, when the neural network is a block structure, the processing apparatus
performs the fusion by taking the block structure as a unit.
When considered individually, these added claim elements further elaborate on the abstract idea identified in the independent claims, because the dependent claim continues to recite the identified abstract idea: “performing directional fusing (e.g., from ending point to starting point) of neural network layers”. The elements in this dependent claim are comparable to receiving/transmitting data, processing data, storing results or transmitting data that serves merely to implement the abstract idea using computing components for performing computer functions (corresponding to the words “apply it” or an equivalent), or merely uses a computer as a tool to perform the identified abstract idea. Thus, it is concluded that these claim elements do not integrate the identified abstract idea (“performing directional fusing (e.g., from ending point to starting point) of neural network layers”) into a practical application (see MPEP 2106.05(f)(2)).
The dependent claim elements have the same relationship to the underlying abstract idea (“performing directional fusing (e.g., from ending point to starting point) of neural network layers”) as outlined in the independent claims analysis above. Thus, it is readily apparent that the dependent claim elements are not directed to any specific improvements of the independent claims and do not practically or significantly alter how the identified abstract idea would be performed. When considered as a whole, as an ordered combination, the dependent claim further elaborates on the previously identified abstract idea (“performing directional fusing (e.g., from ending point to starting point) of neural network layers”).
Therefore, dependent claim 12 is deemed ineligible.
Dependent claims 4, 8-11, 13, 16, 23-25 recite:
wherein layers in the template fuse unit are continuous.
wherein a top layer of continuous layers is an input layer of the template fuse unit, and a last layer of a backward jump is an output layer of the template fuse unit.
wherein the output layer is a single-branch output.
wherein the jump fusion is performed once as n layers are fused every time, wherein n is a natural number.
wherein the starting layer is a top unfused convolution or pooling layer.
wherein the neural network comprises a plurality of main layers,
wherein a main layer is one of matrix multiplication, pooling, and convolution, and the template fuse unit comprises at least two main layers.
wherein the template fuse unit comprises a continuous structure in which a scalar computing layer and a vector computing layer are adjacent,
wherein the scalar computing layer comprises one of an addition layer, a subtraction layer, and a multiplication layer, and
the vector computing layer comprises one of an activation layer, a batch normalization layer, and a scaling layer.
wherein the starting layer is not a convolution or pooling layer.
These further elements in the dependent claims do not perform any claimed method steps. They describe the nature, structure and/or content of other claim elements – the layers; the top layer; the output layer; the jump fusion; the starting layer; the neural network; the main layer; the template fuse unit; the scalar computing layer; the vector computing layer – and as such, cannot change the nature of the identified abstract idea (“performing directional fusing (e.g., from ending point to starting point) of neural network layers”), from a judicial exception into eligible subject matter, because they do not represent significantly more (see MPEP 2106.07). The nature, form or structure of the other claim elements themselves do not practically or significantly alter how the identified abstract idea would be performed and do not provide more than a general link to a technological environment.
Therefore, dependent claims 4, 8-11, 13, 16, 23 are deemed ineligible.
When the dependent claims are considered as a whole, as an ordered combination, the claim elements noted above appear to merely apply the abstract concept to a technical environment in a very general sense. The most significant elements, which form the abstract concept, are set forth in the independent claims. The fact that the computing devices and the dependent claims are facilitating the abstract concept is not enough to confer statutory subject matter eligibility, since their individual and combined significance do not transform the identified abstract concept at the core of the claimed invention into eligible subject matter. Therefore, it is concluded that the dependent claims of the instant application, considered individually, or as a as a whole, as an ordered combination, do not amount to significantly more (see MPEP 2106.07(a)II).
In sum, Claims 1-17, 21-23 are rejected under 35 USC 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION – The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 24, 25 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor regards as the invention.
Claims 24, 25 is rejected under 35 U.S.C. 112(b) because it is a negative limitation that defines a claim by what it’s not, thus not “particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention” (see MPEP 2173.05(i)).
The prior art made of record and not relied upon which, however, is considered pertinent to applicant's disclosure:
US 20070047833 A1 Zhang; Yan et al. System or method for enhancing an image A system and method for enhancing the contrast within an image. An enhanced image can be generated in a real-time or substantially real-time manner from an initial image. A low-contrast image is enhanced, including the visibility of text within the low-contrast image. A logarithm transform method is used to enhance the overall contrast and visibility within the image. A power transform method is used to enhance the visibility and contrast of written text, symbols and other forms of signs within the enhanced image.
US 20210182077 A1 CHEN; Tianshi et al. INFORMATION PROCESSING METHOD AND TERMINAL DEVICE Disclosed are an information processing method and a terminal device. The method comprises: acquiring first information, wherein the first information is information to be processed by a terminal device; calling an operation instruction in a calculation apparatus to calculate the first information so as to obtain second information; and outputting the second information. By means of the embodiments in the present disclosure, a calculation apparatus of a terminal device can be used to call an operation instruction to process first information, so as to output second information of a target desired by a user, thereby improving the information processing efficiency.
US 20200210837 A1 WANG; Jin et al. NETWORK STRUCTURE PROCESSING METHOD AND DEVICE AND RELATED PRODUCTS The disclosure relates to a network structure processing method and device and a related product, including: obtaining, by a computer device, an optimization instruction; and executing a corresponding optimization processing operation on the network structure according to the optimization level in the optimization instruction to obtain an optimized network structure. According to the processing method of the network structure, the resource cost can be reduced, and the detection rate of the network structure on images is improved.
US 20200257960 A1 GABRIEL; James C. et al. COMPRESSED CONVOLUTIONAL NEURAL NETWORK MODELS Systems and processes for training and compressing a convolutional neural network model include the use of quantization and layer fusion. Quantized training data is passed through a convolutional layer of a neural network model to generate convolutional results during a first iteration of training the neural network model. The convolutional results are passed through a batch normalization layer of the neural network model to update normalization parameters of the batch normalization layer. The convolutional layer is fused with the batch normalization layer to generate a first fused layer and the fused parameters of the fused layer are quantized. The quantized training data is passed through the fused layer using the quantized fused parameters to generate output data, which may be quantized for a subsequent layer in the training iteration.
US 20200210821 A1 GUO; Zhibin et al. DATA PROCESSING METHOD, DEVICE, ELECTRONIC DEVICE AND READABLE STORAGE MEDIUM The present disclosure relates to a data processing method, a device, an electronic device, and a readable storage medium. When the above are adopted, a target neural network is subject to a subnet classification. The target neural network includes at least one subnet. When the method is adopted, at least during the process of compiling and running the subnets, only one input operation and one output operation are required. Whereas when the network layers of the subnet are compiled and run layer by layer, pluralities of input operations and output operations are required. Therefore, the data processing method is more efficient and is capable of improving the operation rate.
US 20210182682 A1 MENG; Xiaofu et al. LEARNING TASK COMPILING METHOD OF ARTIFICIAL INTELLIGENCE PROCESSOR AND RELATED PRODUCTS The present disclosure relates to a learning task compiling method of artificial intelligence processors and related products. The learning task compiling method of artificial intelligence processors includes fusing a redundant neural network layer to a convolution layer, optimizing a structure of a convolution neural network, and compiling a learning task of an artificial intelligence processor based on the optimized convolution neural network. The method may achieve high efficiency for learning task compiling of artificial intelligence processors, and may reduce data exchange during processing when being executed on a device.
US 20190303731 A1 Yang; Jinglin TARGET DETECTION METHOD AND DEVICE, COMPUTING DEVICE AND READABLE STORAGE MEDIUM The present disclosure relates to a target detection method and device, a computing device and a readable storage medium. The target detection method include performing target detection using a convolutional neural network comprising a plurality of convolutional layers. The method include performing a branch convolutional process on at least one of the convolutional layers to obtain a branch detection result. The method includes performing a fusion process on the branch detection result, or on the branch detection result and a detection result of a last convolutional layer in the convolutional neural network, and transmitting a result of the fusion process to a fully connected layer.
US 20220066760 A1 Chang; Andre Xian Ming et al. Deep Neural Networks Compiler for a Trace-Based Accelerator A method of compiling neural network code to executable instructions for execution by a computational acceleration system having a memory circuit and one or more acceleration circuits having a maps data buffer and a kernel data buffer is disclosed, such as for execution by an inference engine circuit architecture which includes a matrix-matrix (MM) accelerator circuit having multiple operating modes to provide a complete matrix multiplication. A representative compiling method includes generating a list of neural network layer model objects; fusing available functions and layers in the list; selecting a cooperative mode, an independent mode, or a combined cooperative and independent mode for execution; selecting a data movement mode and an ordering of computations which reduces usage of the memory circuit; generating an ordered sequence of load objects, compute objects, and store objects; and converting the ordered sequence of load objects, compute objects, and store objects into the executable instructions.
Response to Amendments/Arguments
Applicant’s submitted remarks and arguments have been fully considered.
Applicant disagrees with the Office Action conclusions and asserts that the presented claims fully comply with the requirements of 35 U.S.C. § 101 regrading judicial exceptions.
Examiner respectfully disagrees.
With respect to Applicant’s Remarks as to the Claim Objections.
The objection is withdrawn, as a result of the amendments.
With respect to Applicant’s Remarks as to the claims being rejected under 35 USC § 101.
Applicant submits:
a. The pending claims are not directed to an abstract idea.
b. The identified abstract idea is integrated into a practical application.
c. The pending claims amount to significantly more.
Furthermore, Applicant asserts that the Office has failed to meet its burden to identify the abstract idea and to establish that the identified abstract idea is not integrated into a practical application and that the pending claims do not amount to significantly more.
Examiner responds – The arguments have been considered in light of Applicants’ amendments to the claims. The arguments ARE NOT PERSUASIVE. Therefore, the rejection is maintained.
The pending claims, as a whole, are directed to an abstract idea not integrated into a practical application. This is because (1) they do not effect improvements to the functioning of a computer, or to any other technology or technical field (see MPEP 2106.05 (a)); (2) they do not apply or use the abstract idea to effect a particular treatment or prophylaxis for a disease or a medical condition (see the Vanda memo); (3) they do not apply the abstract idea with, or by use of, a particular machine (see MPEP 2106.05 (b)); (4) they do not effect a transformation or reduction of a particular article to a different state or thing (see MPEP 2106.05 (c)); (5) they do not apply or use the abstract idea in some other meaningful way beyond generally linking the use of the identified abstract idea to a particular technological environment, such that the claim as a whole is more than a drafting effort designated to monopolize the exception (see MPEP 2106.05 (e) and the Vanda memo).
In addition, the pending claims do not amount to significantly more than the abstract idea itself.
As such, the pending claims, when considered as a whole, are directed to an abstract idea not integrated into a practical application and not amounting to significantly more.
More specific:
Applicant submits “… claim 1 recites a specific integrated-circuit workflow rooted in the operation of a particular memory hierarchy …”
Examiner has carefully considered, but doesn’t find Applicant’s arguments persuasive.
A “specific integrated-circuit workflow” is not an eligible process (see MPEP 2106.04-07).
Thus, the rejection is proper and has been maintained.
Applicant submits “These limitations define how an integrated circuit manages data movement and constrains fusion growth in view of memory-access cost, which is a technical operation of the computing system, not an abstract mathematical concept.”
Examiner has carefully considered, but doesn’t find Applicant’s arguments persuasive.
“Managing data movement” is not an eligible process (see MPEP 2106.04-07).
Thus, the rejection is proper and has been maintained.
Applicant submits “This is a concrete computing implementation detail, not a result-oriented abstraction.”
Examiner has carefully considered, but doesn’t find Applicant’s arguments persuasive.
“concrete computing implementations” are not limitations that are indicative of integration into a practical application (see MPEP 2106.05)
Thus, the rejection is proper and has been maintained.
Applicant submits “Claim 1 also recites a specific control mechanism that constrains fusion growth based on memory-access cost, thereby addressing a technological problem in neural-network execution.”
Examiner has carefully considered, but doesn’t find Applicant’s arguments persuasive.
“a specific control mechanism” is not indicative of integration into a practical application (see MPEP 2106.05)
Thus, the rejection is proper and has been maintained.
Applicant submits “… it is a concrete mechanism for controlling the TFU expansion with respect to off-chip/on-chip memory traffic.”
Examiner has carefully considered, but doesn’t find Applicant’s arguments persuasive.
See response immediately above.
Thus, the rejection is proper and has been maintained.
Applicant submits “The practical application is an improvement to the internal operation of the computing system (reduced on-chip/off-chip interaction).”
Examiner has carefully considered, but doesn’t find Applicant’s arguments persuasive.
MPEP 2106.04(d)(1) discloses:
An important consideration to evaluate when determining whether the claim as a whole integrates a judicial exception into a practical application is whether the claimed invention improves the functioning of a computer or other technology .... In short, first the specification should be evaluated to determine if the disclosure provides sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. The specification need not explicitly set forth the improvement, but it must describe the invention such that the improvement would be apparent to one of ordinary skill in the art .... Second, if the specification sets forth an improvement in technology. the claim must be evaluated to ensure that the claim itself reflects the disclosed improvement. (Emphasis added)
That is, the claimed invention may integrate the judicial exception into a practical application by demonstrating that it improves the relevant existing technology although it may not be an improvement over well-understood, routine, conventional activity. (Emphasis added)
Thus, the rejection is proper and has been maintained.
Applicant submits “The specification explains that the SRAM is used as a "transfer station" to reduce interaction between on-chip storage and off-chip memory, thereby improving inter-core communication and reducing on-chip/off-chip 1/0 accesses”
Examiner has carefully considered, but doesn’t find Applicant’s arguments persuasive.
See response immediately above.
Thus, the rejection is proper and has been maintained.
Applicant submits “Claim l's DRAM-to-SRAM on-chip unit map formation, TFU creation, and redundancy-based stopping condition are precisely the kinds of concrete limitations that apply the alleged idea in a real-world technological implementation and improve computing performance.”
Examiner has carefully considered, but doesn’t find Applicant’s arguments persuasive.
See response immediately above.
Thus, the rejection is proper and has been maintained.
Applicant submits “Claim I recites an inventive concept in the form of a non-conventional and non-generic ordered combination of elements that improves computer functionality.”
Examiner has carefully considered, but doesn’t find Applicant’s arguments persuasive.
Per Step 2B. Independent claim 1 (which is representative of claims independent 17) does not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when the independent claim is reevaluated as a whole, as an ordered combination under the considerations of Step 2B, the outcome is the same like under Step 2A.2.
Overall, it is concluded that independent claims 1, 17 are deemed ineligible.
Thus, the rejection is proper and has been maintained.
It follows from the above that there are no meaningful limitations in the claims that transform the judicial exception into a patent eligible application such that the claims amount to significantly more than the judicial exception itself. Therefore, the rejection under 35 U.S.C. § 101 is maintained.
With respect to Applicant’s Remarks as to the claims being rejected under 35 USC § 103.
The rejection is withdrawn, as a result of the amendments. The identified prior art does not disclose the following claim elements:
as the fusion proceeds to fuse layers into the template fuse unit,
compute a redundancy percentage as a ratio of the amount of memory access of the on-chip unit map from the DRAM to the SRAM to the amount of normal input/output of the on-chip unit map excluding redundancy, and
stop fusing additional layers into the template fuse unit when the redundancy percentage exceeds a predetermined threshold;
Examiner has reviewed and considered all of Applicant’s remarks. The rejection is maintained, necessitated by the fact that the rejection of the claims under 35 USC § 101 has not been overcome.
Conclusion
THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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Alexandria, VA 22313-1450
or faxed to 571-273-8300
/Radu Andrei/
Primary Examiner, AU 3698