BSPlace: A BLE Swapping technique for placement Minsik Hong George Hwang Hemayamini Kurra Minjun Seo 1

BSPlace: A BLE Swapping technique for placement BLE Level Swapping within Simulated Annealing Chen, Gang, and Jason Cong. "Simultaneous timing driven clustering and placement for FPGAs." Field Programmable Logic and Application. Springer Berlin Heidelberg, Use Rent’s rule to determine swapping method Singh, Amit, Ganapathy Parthasarathy, and Malgorzata Marek- Sadowska. "Efficient circuit clustering for area and power reduction in FPGAs." ACM Transactions on Design Automation of Electronic Systems (TODAES) 7.4 (2002):

Outline iRAC Clustering Comparison Rent’s Rule Key terms Clustering Step Results SCPlace Introduction 3

4 Efficient circuit clustering for area and power reduction in FPGAs. Singh, Amit, Ganapathy Parthasarathy, and Malgorzata Marek-Sadowska. ACM Transactions on Design Automation of Electronic Systems (TODAES) 7.4 (2002):

Clustering Comparison TVPACK What is different in RPACK? Gain functions for considering routing constraints in cost function while clustering RPACK  iRAC Rent’s rule to depopulate the clusters!!  Best CW 5

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Rent’s Rule Where N io is the number of inputs and outputs in a CLB K is the average number of connections per BLE Calculate k in technology mapping phase B is the number of BLEs in a CLB P is the rent’s parameter Since FPGA has uniform interconnect resources, p at local level is assu med to be uniform Characterize the complexity of a cluster Smaller values of p mean that the cluster’s external routing requirement is low So, a good clustering solution will ensure that the Rent’s parameter of the generated cluster is small. 7

Net Length : Local Rent’s parameter P l d Complexity Varies across design. Solution – Use local interconnect complexity measure ba sed in interconnect length distributions. (Van Marck et al., 95) Reduces to Rent’s exponent for uniform design at the top l evel 8

Net Length : Rent’s Parameter Van Marck, Stroobandt, Campenhout, 1995 p =  (log N i ) /  (log L i ) p – Rent’s parameter L i - length of a net N i - number of nets of length L i First Order Approximation for varying rent’s parameter Connects net-length with Rent’s parameter! Wirelength, channel width, routability estimation based on Rent’s p arameter 9

Applications of Rent’s Rule layout parameter estimations in Electronic Design Automa tion, studies of new computer architectures, and the generation of synthetic circuit benchmarks. 10

Applications of Rent’s Rule The increasing problem sizes in electronic design and the sub-micron design challenges have placed the need for a priori estimates of chip layout parameters in the forefront. The generality and predictive power of Rent’s rule are perfect for suc h estimates. Another application of Rent’s rule tries to assess the merits of new chip or computer architectures before they have to be built, using wire length estimates based on Rent’s rule a nd a generic model for the architecture. This research has gained attention especially due to the possibilities of using optical interconnections to build three-dimensional chips 11

Key terms Degree of an BLE the number of nets incident to that BLE Separation of an BLE The sum of all terminals of nets incident to the BLE Connectivity factor (c) Weight, w(e) 12

Clustering step (1) 13 First, calculate the connectivity factor of all unclustered BLEs. BLE NET Terminal Cluster

Clustering step (1) 14 First, calculate the c factor of all unclustered BLEs. Degree - the number of nets incident to BLE A

Clustering step (1) First, calculate the c factor of all unclustered BLEs. Degree - the number of nets incident to BLE A Separation - the sum of all terminals of nets incident to the BLE A

Clustering step (2) Second, choose a seed Degree = 4, c=1.125 Degree = 4, c= Cluster size = 5 which has highest degree and lowest c

Clustering step (3) Third, assign gain value to unclustered BLEs and cho ose BLE which has highest gain 17 the attraction of ble X to ble C x: the net between ble X and ble C n: the cluster size (# of BLEs in CLB) w(x): the weight of net α: the number of pins of net x already inside

Clustering step (3) 18 Cluster size = 4 n: the cluster size (# of BLEs in CLB) α: the number of pins of net x already inside

Clustering step (3) 19 y z w Cluster size = 4

Clustering step (3) 20 If adding X to C fully absorbs net x, then G(X,C,x) is multiplied by a large constant value k. (ex. k=10) Cluster size = 4 choose BLE which has highest gain

Clustering step (4) Fourth, check spatial uniformity using Rent’s rule where K=3, B=4, P=0.5 Threshold T io = 6 If N io > T io, then choose th at BLE as another seed. 21 # of used I/O of cluster < T io p < P Smaller values of p mean that the cluster’s external routing requirement is low

Results(1) 22 Random Seed of RPack iRAC is more effective in clustering circuits which have a higher percentage of low-fanout nets. Why?

Result(2) iRAC is able to lower the number of external nets, and the Rent’s parameter of the circuits after cl ustering! 23

24 Simultaneous timing driven clustering and placement for FPGAs. Chen, Gang, and Jason Cong. Field Programmable Logic and Application. Springer Berlin Heidelberg,

Why simultaneous placement and clustering? 25

Why simultaneous placement and clustering? More freedom of changing to change a circuit structure but fast and accurate estimation of wirelength, timing and routability are not available in clustering stage In placement stage due to the fixed circuit structure, simultaneous optimization of wirelength, timing and routability are possible. Sub-optimal place and route result!!!! 26

Key concept Fragment level move BLE to a new CLB Check for valid CLB configuration Feasibility (number of BLEs and input pins) Update the cost function Block level move CLB to CLB Logic duplication 27

To be Continued…. 28